Week 1: Overview of SAP Analytics Cloud (SAC)

Introduction: SAP Analytics Cloud (SAC) is a cloud-based platform that integrates business intelligence (BI), planning, and predictive analytics into a single solution. This week introduces SAC, its purpose, and its role in modern data-driven decision-making. The emphasis is on practical usage, guiding you through setting up a trial account and exploring SAC’s core functionalities to understand its value proposition.

Learning Objectives: By the end of this week, you will be able to:

• Describe what SAP Analytics Cloud is and its primary functions.
• Identify SAC’s role in business intelligence, planning, and predictive analytics.
• Sign up for an SAC trial account and access the platform.
• Explore SAC’s home interface and basic features.
• Understand how SAC fits into the SAP ecosystem and broader analytics landscape.

Scope: This week provides an overview of SAC, kicking off the 10-week course. It covers SAC’s purpose, core components, and initial setup, preparing you for Week 2’s exploration of key features and capabilities.

Background Information: SAP Analytics Cloud is a Software-as-a-Service (SaaS) platform built on the SAP Business Technology Platform (BTP) and SAP HANA Cloud. Key points include:

• Purpose: SAC unifies BI, enterprise planning, and predictive analytics, enabling users to visualize data, create plans, and forecast outcomes in one environment.
• Core Components: Business Intelligence: Data visualization, dashboards, and reporting. Planning: Collaborative financial, operational, and supply chain planning. Predictive Analytics: Machine learning and AI-driven insights (e.g., Smart Insights, predictive forecasting).
• Key Benefits: Single platform for analytics and planning, reducing tool fragmentation. Native integration with SAP systems (e.g., S/4HANA, BW/4HANA). User-friendly interface for business users, minimizing coding needs. Cloud-based scalability and accessibility.
• Use Cases: Organize data (e.g., sales records, budgets). Perform quick calculations or formatting. Set up datasets for analysis or reporting.
• Challenges: Learning curve for non-SAP users. Dependency on SAP ecosystem for optimal integration. Cost considerations for large-scale deployments.

Hands-On Example:

Scenario: You’re a business analyst tasked with exploring SAP Analytics Cloud to evaluate its potential for your organization. You’ll sign up for a free SAC trial, access the platform, and explore its home interface to understand its core functionalities.

Prerequisites:

• A computer with a modern browser (e.g., Chrome, Edge, Firefox).
• An email address to sign up for the SAC trial.
• Internet connection.
• No prior SAP software installation required (SAC is cloud-based).

Step-by-Step Instructions:

Sign Up for SAC Trial:

Visit the SAP Analytics Cloud trial page: https://www.sap.com/products/technology-platform/analytics-cloud.html#try-now.

Click “Start your free trial” or similar (exact wording may vary).

Complete the registration form with your name, email, and company details.

Verify your email via the confirmation link sent by SAP.

Log in to the SAP trial portal using your credentials.

Expected Outcome: Access to a 30-day SAC trial environment with preloaded sample data and templates.

Access the SAC Platform:

After logging in, you’ll be redirected to the SAC home page (URL typically like https://<tenant>.sapanalytics.cloud/).

Note the tenant ID (e.g., us10 or eu10), as it’s unique to your trial.

Verify: The home page loads with a welcome message and options like “Create,” “Files,” and “Home.”

Troubleshooting:

If login fails, check your email for verification or reset your password.

Ensure browser compatibility (disable pop-up blockers if needed).

Explore the Home Interface:

Home Page Overview:

Top Menu: Includes “Home,” “Files,” “Create,” “Browse,” and user profile settings.

Create Menu: Options to create Stories, Analytic Applications, Models, or Plans.

Recent Files: Displays sample dashboards or stories (e.g., “Sales Performance”).

Quick Actions: Tiles for creating a new story, dataset, or planning model.

Click “Home” to view the dashboard with widgets (e.g., recent files, tasks).

Click “Files” to browse sample content (e.g., folders like “Samples” or “Public”).

Open a sample story (e.g., “Sales Dashboard”):

Click on a sample file under “Files” > “Samples.”

Observe visualizations like charts, tables, or KPIs.

Interact by clicking filters (e.g., filter by region or product).

Expected Outcome: Familiarity with the home interface and ability to view a sample dashboard.

Screenshot Tip: Take a screenshot of the home page and a sample story for reference.

Explore Core Functionalities:

Create a Test Story:

From the home page, click “Create” > “Story.”

Select “Canvas” mode for free-form layout.

Add a sample dataset (e.g., “BestRunJuice_SampleModel” from the trial).

Insert a bar chart:

Click the “Chart” icon in the toolbar.

Drag “Sales Revenue” to the Y-axis and “Region” to the X-axis.

Save the story as “My_First_Story” in the “Public” folder.

Verify: The chart displays sales by region (e.g., North, South).

Explore Planning:

From “Create,” select “Planning Model.”

Browse sample planning templates (e.g., “Financial Planning”).

Note features like input fields for budgeting or forecasting.

Explore Predictive Analytics:

In your story, click “Smart Insights” (if available) on the chart.

Observe AI-driven suggestions (e.g., key drivers of sales).

Validate and Troubleshoot:

Validation:

Confirm trial access: Home page loads with sample content.

Verify sample story: Visualizations (e.g., charts) are interactive.

Check test story: “My_First_Story” saved and displays a bar chart.

Ensure planning and predictive features are accessible (may be limited in trial).

Troubleshooting:

Login Issues: Clear browser cache or try a different browser.

Missing Samples: Ensure you’re in the “Samples” folder under “Files.”

Story Errors: Verify dataset selection; use sample data if custom data fails.

Slow Performance: Check internet connection; SAC is cloud-based.

Support: Use SAP’s trial support page (accessible via the trial portal) or community forums: https://community.sap.com/.

Clean Up:

Save your test story (“My_First_Story”) for future reference.

Log out of SAC via the user profile menu (top-right corner).

Keep trial account active for subsequent weeks (valid for 30 days).

Interpretation: This hands-on example introduces SAP Analytics Cloud by guiding you through trial setup and interface exploration. By creating a simple story and interacting with sample content, you gain practical experience with SAC’s unified BI, planning, and predictive analytics, setting the stage for deeper exploration in Week 2.

Supplemental Information: SAP Analytics Cloud Overview: https://www.sap.com/products/technology-platform/analytics-cloud.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud. Gartner Magic Quadrant 2024: https://www.gartner.com/en/documents/5097147.

Discussion Points:

• How does SAC’s unified approach (BI, planning, predictive) benefit organizations?
• What advantages does SAC’s cloud-based nature offer over on-premises tools?
• How might SAC’s SAP-centric design impact non-SAP users?
• What initial impressions do you have of SAC’s interface compared to other tools?
• How can SAC support data-driven decision-making in your industry?

Week 2: Key Features and Capabilities

Introduction: SAP Analytics Cloud (SAC) offers a robust set of features that integrate business intelligence (BI), planning, and predictive analytics into a single cloud-based platform. This week focuses on exploring SAC’s key features—data visualization, collaborative planning, predictive analytics, and augmented analytics—through practical application. The emphasis is on hands-on usage, enabling you to create visualizations, interact with planning models, and experiment with predictive tools in the SAC trial environment.

Learning Objectives: By the end of this week, you will be able to:

• Identify SAC’s core features and their business applications.
• Create and customize data visualizations (charts, tables) in a story.
• Interact with planning models to input and analyze data.
• Use predictive analytics features like Smart Insights and Smart Predict.
• Validate feature usage and troubleshoot common issues in SAC.

Scope: This week dives into SAC’s key features and capabilities, building on Week 1’s overview of the platform. It covers practical usage of BI, planning, and predictive tools, preparing for Week 3’s exploration of SAC architecture and deployment models.

Background Information: SAC’s key features empower users to analyze, plan, and predict with ease:

• Data Visualization (BI): Create interactive dashboards, charts, and tables. Supports diverse chart types (e.g., bar, line, geo maps). Features like filters, drill-downs, and linked analysis enhance interactivity.
• Collaborative Planning: Build financial, operational, or workforce plans. Supports data input, version control, and collaborative workflows. Integrates actuals and forecasts for real-time planning.
• Predictive Analytics: Smart Insights: AI-driven analysis of data patterns. Smart Predict: Automated machine learning for forecasting and classification. Smart Discovery: Identifies key influencers in datasets.
• Augmented Analytics: Natural language query (NLQ) for asking data questions. Automated chart recommendations based on data.
• Key Benefits: Intuitive interface for non-technical users. Seamless integration with SAP systems (e.g., S/4HANA). Scalable cloud architecture for large datasets.
• Applications: Visualize sales trends for retail. Plan budgets for finance teams. Forecast demand using predictive models.
• Challenges: Limited customization in trial environments. Learning predictive tools requires understanding data context. Performance may vary with large datasets or complex visualizations.

Hands-On Example:

Scenario: You’re a business analyst evaluating SAC’s features for your organization. Using the SAC trial, you’ll create a story with visualizations, interact with a planning model, and explore predictive analytics to analyze a sample sales dataset, gaining hands-on experience with SAC’s core capabilities.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s home interface (from Week 1).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” (available in trial) or a similar sales dataset.
• Modern browser (e.g., Chrome, Edge) and internet connection.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify access to the home page with options like “Create,” “Files,” and “Home.”

Navigate to “Files” > “Samples” to locate the “BestRunJuice_SampleModel” or a similar sales dataset.

Troubleshooting:

If login fails, reset your password via the SAP trial portal.

Ensure browser compatibility (clear cache if needed).

Create a Story with Data Visualizations:

From the home page, click “Create” > “Story” > “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Confirm dimensions (e.g., Region, Product) and measures (e.g., Sales Revenue).

Create a bar chart:

Click the “Chart” icon in the toolbar.

Choose “Bar/Column” chart type.

Drag “Sales Revenue” to the Y-axis and “Region” to the X-axis.

Customize: Add a title (e.g., “Sales by Region”), adjust colors, and enable data labels.

Add a table:

Click “Table” in the toolbar.

Add columns: “Product,” “Sales Revenue,” “Quantity Sold.”

Apply a filter: Click the filter icon, select “Region,” and filter for “North.”

Save the story:

Click “Save” > Name it “Sales_Analysis_Story” > Save in “Public” folder.

Verify: Bar chart shows sales by region; table lists filtered data for North.

Expected Outcome: Interactive story with a bar chart and table, demonstrating BI capabilities.

Interact with a Planning Model:

From “Create,” select “Planning Model.”

Choose a sample planning model (e.g., “Financial Planning” or “Sales Planning” in “Samples”).

Explore the model:

View dimensions (e.g., Time, Account, Region).

Open a planning table (click “Table” in the model interface).

Input data: Edit a cell (e.g., increase “Sales Forecast” for Q1 2025 by 10%).

Save the changes: Click “Save” > “Save Data.”

Create a planning visualization:

In the planning model, add a line chart.

Plot “Sales Forecast” over “Time” (e.g., quarters).

Observe the updated forecast reflecting your input.

Verify: Planning table accepts input; line chart reflects changes.

Expected Outcome: Hands-on experience with planning workflows, showing collaborative planning features.

Troubleshooting:

If no planning models are available, use a sample story with planning data.

Ensure edit permissions in the trial (some models may be read-only).

Explore Predictive Analytics:

Open your “Sales_Analysis_Story” from step 2.

Use Smart Insights:

Select the bar chart (Sales by Region).

Click “Smart Insights” (lightbulb icon, if available).

Review AI-driven insights (e.g., “Region X drives 40% of sales due to high product demand”).

Use Smart Predict:

From “Create,” select “Predictive Scenario.”

Choose “Time Series Forecasting.”

Select “BestRunJuice_SampleModel” > “Sales Revenue” as the target.

Set “Time” as the date dimension (e.g., Month).

Run the forecast (default settings).

View the output: Predicted sales for future periods (e.g., next 6 months).

Save the predictive scenario as “Sales_Forecast” in “Public.”

Verify: Smart Insights provides actionable findings; Smart Predict generates a forecast chart.

Expected Outcome: Practical use of predictive tools, showcasing SAC’s AI capabilities.

Troubleshooting:

If Smart Insights is unavailable, ensure the chart is selected.

For Smart Predict, verify the dataset has time-series data; note restrictions for Enterprise licenses.

Validate and Troubleshoot:

Validation:

Confirm story: “Sales_Analysis_Story” includes a bar chart (sales by region) and a filtered table (North region).

Verify planning: Edited forecast value saved and reflected in the line chart.

Check predictive analytics: Smart Insights provides insights; “Sales_Forecast” predicts future sales.

Ensure interactivity: Filters and drill-downs work in the story.

Troubleshooting:

Data Issues: Confirm “BestRunJuice_SampleModel” is loaded; switch to another sample if unavailable.

Feature Access: Some predictive features may be limited in trial; use sample stories if restricted.

Performance: Refresh the browser if SAC lags; check internet connection.

Save Errors: Ensure you have write permissions in the “Public” folder.

Support: Access SAP Community (https://community.sap.com/topics/analytics-cloud) or trial help portal.

Clean Up:

Save “Sales_Analysis_Story” and “Sales_Forecast” for future reference.

Log out of SAC via the user profile menu (top-right corner).

Keep the trial account active for subsequent weeks (valid for 30 days).

Interpretation: This hands-on example demonstrates SAC’s key features—data visualization, planning, and predictive analytics—through practical tasks in the trial environment. By creating a story, editing a planning model, and using predictive tools, you gain a deeper understanding of SAC’s capabilities, preparing for Week 3’s focus on architecture and deployment.

Supplemental Information: SAC Features Overview: https://www.sap.com/products/technology-platform/analytics-cloud/features.html. SAP Help Portal for SAC: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD. SAP Community: https://community.sap.com/topics/analytics-cloud.

Discussion Points:

• How do SAC’s visualization tools compare to other BI platforms you’ve used?
• What benefits does collaborative planning offer for cross-functional teams?
• How can predictive analytics like Smart Predict enhance decision-making?
• What challenges might arise when scaling SAC features to large datasets?
• How does SAC’s user-friendly design impact adoption in organizations?

Week 3: SAC Architecture and Deployment Models

Introduction: Understanding the architecture and deployment models of SAP Analytics Cloud (SAC) is crucial for leveraging its capabilities effectively. This week focuses on SAC’s technical architecture, its underlying components, and the deployment options available (public, private, and hybrid cloud). The emphasis is on practical usage, guiding you through exploring SAC’s architecture by connecting to a sample data source and reviewing deployment settings in the trial environment.

Learning Objectives: By the end of this week, you will be able to:

• Describe SAC’s technical architecture and its key components.
• Understand the role of SAP Business Technology Platform (BTP) and SAP HANA Cloud in SAC.
• Identify SAC’s deployment models (public, private, hybrid) and their use cases.
• Connect to a sample data source in SAC to explore its data integration architecture.
• Review deployment settings in the SAC trial to understand cloud configuration.

Scope: This week covers SAC’s architecture and deployment models, building on Week 1’s overview and Week 2’s exploration of key features. It prepares for Week 4’s focus on navigating the SAC interface by providing a technical foundation for how SAC operates in the cloud.

Background Information: SAC’s architecture and deployment models enable scalable, secure, and integrated analytics:

• Architecture Overview: SAP Business Technology Platform (BTP): SAC is built on BTP, providing cloud services like integration, extension, and data management. SAP HANA Cloud: The in-memory database powering SAC’s data processing, analytics, and planning.
• Components: Frontend: Browser-based interface for stories, dashboards, and planning. Backend: HANA Cloud for data storage, computation, and predictive analytics. Integration Layer: Connects to SAP (e.g., S/4HANA, BW/4HANA) and non-SAP data sources (e.g., Excel, SQL databases). Security: Role-based access, encryption, and single sign-on (SSO).
• Data Connectivity: Live Connections: Real-time access to data without replication (e.g., SAP HANA, SAP BW). Import Connections: Data uploaded to SAC’s HANA Cloud (e.g., CSV, Excel). Supports OData, JDBC, and SAP connectors.
• Deployment Models: Public Cloud: Hosted by SAP, fully managed, ideal for standard analytics needs. Private Cloud: Dedicated environment, managed by SAP or partners, for enhanced control. Hybrid Cloud: Combines public/private clouds with on-premises systems.
• Applications: Public cloud for small-to-medium businesses needing quick analytics. Private cloud for regulated industries (e.g., finance, healthcare). Hybrid for enterprises with mixed SAP/non-SAP environments.
• Challenges: Selecting the right deployment model for organizational needs. Managing live vs. import connections for performance. Ensuring compliance with data residency and security policies.

Hands-On Example:

Scenario: You’re a business analyst tasked with understanding SAC’s architecture to recommend a deployment model for your organization. You’ll connect to a sample data source, explore data integration, and review deployment settings to gain insight into SAC’s cloud-based architecture.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s home interface (from Week 1).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” (available in trial) or a similar sales dataset.
• Modern browser (e.g., Chrome, Edge) and internet connection.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Create,” “Files,” and “Home.”

Navigate to “Files” > “Samples” to locate the “BestRunJuice_SampleModel” or a similar sales dataset.

Troubleshooting:

If login fails, reset your password via the SAP trial portal.

Ensure browser compatibility (clear cache if needed).

Explore Data Connectivity (Architecture):

Create a new model to explore SAC’s data integration:

From the home page, click “Create” > “Model.”

Select “Use a datasource” > “Import Data” > “Data uploaded from a file or acquired.”

Choose “BestRunJuice_SampleModel” (or equivalent) as the data source.

Review the model creation wizard:

Data Mapping: Confirm dimensions (e.g., Region, Product) and measures (e.g., Sales Revenue).

Connection Type: Note that this is an import connection (data copied to SAC’s HANA Cloud).

Save the model as “Sales_Model” in the “Public” folder.

Verify the model:

Open “Sales_Model” from “Files” > “Public.”

Check the data preview to ensure columns like “Region” and “Sales Revenue” are present.

Explore live connection (if available):

In the model creation wizard, select “Live Data Connection” (if enabled in trial).

Note options like “SAP HANA” or “SAP BW” (trial may limit live connections).

Verify: Model created successfully; data preview shows expected structure.

Expected Outcome: Understanding of import vs. live connections in SAC’s architecture.

Troubleshooting:

If the sample model is missing, use another sample dataset from “Samples.”

Ensure sufficient trial permissions for model creation.

Create a Story Using the Model:

From “Create,” select “Story” > “Canvas” mode.

Add the “Sales_Model” as the data source:

Click “Add Data” > “Data from a Model” > Select “Sales_Model.”

Create a visualization:

Add a “Bar/Column” chart.

Drag “Sales Revenue” to the Y-axis and “Region” to the X-axis.

Add a title: “Regional Sales Overview.”

Save the story as “Architecture_Story” in “Public.”

Verify: Chart displays sales by region, confirming data flows from HANA Cloud to the frontend.

Expected Outcome: Practical experience with SAC’s architecture, from data storage to visualization.

Review Deployment Settings:

Explore system settings to understand the trial’s deployment:

Click the user profile (top-right) > “System” > “About.”

Note details:

Tenant ID: Unique identifier (e.g., us10, eu10).

Version: SAC version (e.g., 2025.x.x).

Region: Data center location (e.g., US, EU).

This indicates a public cloud deployment hosted by SAP.

Check data source connectivity:

Navigate to “Files” > “Connections” (if accessible in trial).

Observe sample connections (e.g., “SAP HANA” or “File Server” for imports).

Verify: Tenant details confirm public cloud deployment; connections show integration capabilities.

Expected Outcome: Insight into SAC’s cloud deployment and data connectivity.

Troubleshooting:

If “Connections” is restricted, rely on sample model behavior to infer architecture.

Contact SAP trial support if system details are inaccessible.

Validate and Troubleshoot:

Validation:

Confirm model: “Sales_Model” created with correct dimensions and measures.

Verify story: “Architecture_Story” displays a bar chart of sales by region.

Check deployment: “About” page shows public cloud details (tenant, region).

Ensure data connectivity: Model uses import connection; live connection options noted (if available).

Troubleshooting:

Model Errors: Verify data source selection; retry with another sample if needed.

Story Issues: Ensure “Sales_Model” is linked correctly; check chart settings.

Access Restrictions: Trial may limit live connections or system settings; use sample data and “About” page.

Performance: Refresh browser if SAC lags; check internet connection.

Support: Use SAP Community (https://community.sap.com/topics/analytics-cloud) or trial help portal.

Clean Up:

Save “Sales_Model” and “Architecture_Story” for future reference.

Log out of SAC via the user profile menu (top-right corner).

Keep trial account active for subsequent weeks (valid for 30 days).

Interpretation: This hands-on example provides practical experience with SAC’s architecture by creating a model and story, and reviewing deployment settings in the trial environment. By exploring data connectivity and cloud infrastructure, you gain a technical understanding of how SAC operates, preparing for Week 4’s focus on interface navigation.

Supplemental Information: SAC Architecture Overview: https://www.sap.com/products/technology-platform/analytics-cloud/technical.html. SAP BTP Documentation: https://help.sap.com/docs/BTP. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud.

Discussion Points:

• How does SAC’s HANA Cloud backend enhance performance compared to traditional databases?
• What are the trade-offs between public, private, and hybrid deployments?
• How do live vs. import connections impact data workflows in SAC?
• What role does BTP play in SAC’s scalability and integration?
• How might deployment choices affect compliance in regulated industries?

Week 4: Navigating the SAC Interface

Introduction: Navigating the SAP Analytics Cloud (SAC) interface effectively is essential for leveraging its business intelligence, planning, and predictive analytics capabilities. This week focuses on mastering the SAC interface, including the home page, main menu, story builder, and other key components. The emphasis is on practical usage, guiding you through navigating the trial environment to create a story and interact with interface features.

Learning Objectives: By the end of this week, you will be able to:

• Identify and navigate key components of the SAC interface (home page, main menu, story builder).
• Use the interface to create and customize a story with visualizations.
• Explore tools like filters, data explorer, and collaboration features.
• Save and organize content in the SAC file structure.
• Troubleshoot navigation issues in the trial environment.

Scope: This week covers navigating the SAC interface, building on Week 1’s overview, Week 2’s key features, and Week 3’s architecture and deployment models. It prepares for Week 5’s exploration of licenses and editions by ensuring proficiency in using SAC’s user-friendly interface for analytics tasks.

Background Information: SAC’s interface is designed for business users, offering intuitive navigation and powerful tools:

• Key Interface Components: Home Page: Central hub with recent files, quick actions (e.g., create story), and personalized widgets. Main Menu: Includes “Home,” “Files,” “Create,” “Browse,” “Calendar,” and user profile settings. Story Builder: Canvas for creating dashboards with charts, tables, and filters. Data Explorer: Tool for analyzing data, applying filters, and creating ad-hoc visualizations. Files Area: Organizes models, stories, and datasets in folders (e.g., Public, Samples). Collaboration Tools: Comments, sharing, and version history for team workflows.
• Navigation Features: Create Menu: Options for stories, models, analytic applications, and planning models. Toolbar: Tools for adding charts, tables, filters, and predictive features in stories. Search Bar: Quick access to files, models, or help resources.
• Applications: Build sales dashboards in the story builder. Organize project files in the Files area. Collaborate on planning models with team members.
• Challenges: Navigating nested menus in complex stories. Managing file permissions in trial environments. Understanding context-sensitive tools (e.g., story vs. model interfaces).

Hands-On Example:

Scenario: You’re a business analyst tasked with creating a sales dashboard in SAC. You’ll navigate the SAC trial interface to create a story, add visualizations, apply filters, and explore collaboration features, gaining practical experience with the interface’s key components.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s features and architecture (from Weeks 1–3).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model.
• Modern browser (e.g., Chrome, Edge) and internet connection.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Navigate the Home Page:

Explore the home page:

Quick Actions: Note tiles for “Create Story,” “Create Model,” or “Create Dataset.”

Recent Files: View sample stories (e.g., “Sales Performance”) or your previous work.

Widgets: Observe personalized content like tasks or pinned files.

Use the Search Bar (top-right):

Search for “BestRunJuice” to locate the sample model.

Verify results show “BestRunJuice_SampleModel” under “Files” > “Samples.”

Create a Story Using the Story Builder:

Navigate to “Create” > “Story” > Select “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Build visualizations:

Bar Chart:

Click the “Chart” icon in the toolbar.

Drag “Sales Revenue” to the Y-axis and “Region” to the X-axis.

Add a title: “Sales by Region.”

Pie Chart:

Add another chart via the “Chart” icon.

Select “Pie” chart type.

Drag “Sales Revenue” to “Measures” and “Product” to “Color.”

Apply a filter:

Click “Filter” in the toolbar.

Select “Region” and filter for “North” and “South.”

Save the story:

Click “Save” > Name it “Navigation_Story” > Save in “Public” folder.

Explore the Data Explorer:

In “Navigation_Story,” click “Data Explorer” (icon or tab).

Analyze the dataset:

Select “BestRunJuice_SampleModel.”

Drag “Sales Revenue” and “Quantity Sold” to a new table.

Use Collaboration and File Management:

Share the story:

In “Navigation_Story,” click “Share.”

Add a comment: “Review sales dashboard for feedback.”

Organize files:

Navigate to “Files” > “Public.”

Create a new folder: “Week4_Projects.”

Validate and Troubleshoot:

Validation:

Confirm home page navigation.

Verify story creation.

Troubleshooting:

Address common issues.

Interpretation: This hands-on example builds proficiency in navigating the SAC interface by creating a story, exploring data, and managing files in the trial environment. By mastering the home page, story builder, Data Explorer, and collaboration tools, you prepare for Week 5’s focus on licenses and editions.

Supplemental Information: SAC User Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud. SAC Interface Tutorials: https://www.sap.com/products/technology-platform/analytics-cloud/resources.html.

Discussion Points:

• How does SAC’s interface design support non-technical users?
• What are the benefits of the Data Explorer for ad-hoc analysis?
• How can collaboration features enhance team workflows in SAC?
• What navigation challenges might arise in complex SAC projects?
• How does SAC’s file management compare to other BI tools?

Week 5: Understanding Licenses and Editions

Introduction: Understanding SAP Analytics Cloud (SAC) licenses and editions is critical for selecting the right plan to meet organizational needs. This week focuses on SAC’s licensing structure, available editions, and their impact on feature access and user roles. The emphasis is on practical usage, guiding you through the SAC trial environment to explore user roles, feature availability, and licensing implications.

Learning Objectives: By the end of this week, you will be able to:

• Identify SAC’s licensing models and editions (e.g., Business Intelligence, Planning).
• Understand the differences between user types (e.g., Viewer, Standard, Planning).
• Explore user roles and feature access in the SAC trial environment.
• Assess how licensing impacts SAC functionality and scalability.
• Troubleshoot licensing-related issues in the trial.

Scope: This week covers SAC’s licenses and editions, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, and Week 4’s interface navigation. It prepares for Week 6’s comparison with other BI tools by providing insight into SAC’s licensing structure and its practical implications.

Background Information: SAC’s licensing is designed to support diverse analytics and planning needs:

• Editions: Business Intelligence (BI): Focuses on data visualization, reporting, and basic predictive analytics. Planning: Includes BI features plus collaborative planning, budgeting, and forecasting. Enterprise: Combines BI, planning, and advanced features like predictive scenarios and custom applications (availability may vary).
• User Types: Viewer: Read-only access to stories and dashboards; limited interactivity (e.g., apply filters). Standard (BI User): Create and edit stories, access BI and basic predictive features. Planning Standard/Professional: Access planning models, input data, and advanced planning workflows. Admin: Manages users, roles, and system settings.
• Licensing Model: Subscription-based, typically per user per month. Pricing varies by edition and user type (specific pricing not covered; refer to https://www.sap.com/products/technology-platform/analytics-cloud/pricing.html). Trial includes a mix of BI and planning features with admin access, but some features (e.g., advanced predictive, multi-user collaboration) may be restricted.
• Key Considerations: Feature Access: Planning features require Planning licenses; predictive tools may need Enterprise. Scalability: Viewer licenses are cost-effective for large user bases; Standard/Planning for active contributors. Roles: Custom roles define granular permissions (e.g., edit specific models).
• Applications: BI licenses for sales teams needing dashboards. Planning licenses for finance teams managing budgets. Mixed licenses for cross-functional analytics and planning.
• Challenges: Aligning licenses with user needs to avoid over- or under-provisioning. Navigating trial limitations to understand full feature access. Managing costs for large-scale deployments.

Hands-On Example:

Scenario: You’re a business analyst evaluating SAC’s licensing options for your organization. Using the SAC trial, you’ll explore user roles, test feature access (BI, planning, predictive), and assess how licensing affects functionality, gaining practical insight into SAC’s editions and user types.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface and features (from Weeks 1–4).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model.
• Modern browser (e.g., Chrome, Edge) and internet connection.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Explore User Roles and System Settings:

Check your user role:

Click the user profile (top-right) > “System” > “About.”

Note the user ID and role (trial typically assigns an admin-like role with BI and planning access).

Navigate to “Security” (if accessible):

Go to “Browse” > “Security” > “Users” or “Roles.”

Observe predefined roles (e.g., BI Content Creator, Planning Modeler) and permissions:

BI Content Creator: Create/edit stories, access BI tools.

Planning Modeler: Edit planning models, input data.

Test BI Features (Standard User Access):

Create a new story to test BI functionality:

From “Create” > “Story” > Select “Canvas” mode.

Add “BestRunJuice_SampleModel” as the data source.

Create a bar chart:

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “BI Sales by Region.”

Test Planning Features (Planning User Access):

Access a planning model:

From “Create” > “Planning Model.”

Select a sample planning model (e.g., “Sales Planning” in “Samples”).

Test Predictive Features (Enterprise Access):

Open the story.

Use Smart Insights and Smart Predict.

Validate and Troubleshoot:

Validation:

Confirm role and feature access.

Troubleshooting:

Address trial restrictions.

Interpretation: This hands-on example provides practical insight into SAC’s licenses and editions by testing BI, planning, and predictive features in the trial environment. By exploring user roles and feature access, you gain an understanding of how licensing impacts SAC usage, preparing for Week 6’s comparison with other BI tools.

Supplemental Information: SAC Licensing Guide: https://www.sap.com/products/technology-platform/analytics-cloud/pricing.html. SAP Help Portal for SAC: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD. SAP Community: https://community.sap.com/topics/analytics-cloud.

Discussion Points:

• How do SAC’s user types (Viewer, Standard, Planning) align with organizational roles?
• What are the cost-benefit trade-offs of BI vs. Planning licenses?
• How might trial limitations affect your evaluation of SAC’s editions?
• Why is role-based access important for SAC deployments?
• How can licensing choices impact scalability in large organizations?

Week 6: SAC vs Other BI Tools (Power BI, Tableau)

Introduction: SAP Analytics Cloud (SAC) is a leading business intelligence (BI) platform, but how does it compare to competitors like Microsoft Power BI and Tableau? This week focuses on comparing SAC’s features, strengths, and limitations against Power BI and Tableau, emphasizing visualization, analytics, and integration capabilities. The practical usage emphasis involves creating a dashboard in SAC to replicate common BI tasks, allowing you to experience SAC’s approach firsthand and contrast it with Power BI and Tableau.

Learning Objectives: By the end of this week, you will be able to:

• Compare SAC, Power BI, and Tableau in terms of visualization, analytics, and integration.
• Identify SAC’s unique strengths (e.g., planning, SAP integration) and limitations.
• Create a dashboard in SAC with visualizations and filters to compare with Power BI/Tableau workflows.
• Evaluate feature differences based on hands-on SAC usage.
• Understand use cases where SAC excels over competitors.

Scope: This week compares SAC with Power BI and Tableau, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, and Week 5’s licenses and editions. It prepares for Week 7’s exploration of SAP Cloud Platform integration by highlighting SAC’s competitive positioning in the BI landscape.

Background Information: SAC, Power BI, and Tableau are top BI platforms, each with distinct strengths:

• SAP Analytics Cloud (SAC): Strengths: Unified BI, planning, and predictive analytics in one platform. Native integration with SAP systems (e.g., S/4HANA, BW/4HANA). Cloud-based, built on SAP Business Technology Platform (BTP) and HANA Cloud. Augmented analytics (Smart Insights, Smart Predict) for AI-driven insights. Collaborative planning for budgeting and forecasting. Limitations: Higher learning curve for non-SAP users. Optimal performance with SAP data sources. Potentially higher costs for advanced features (e.g., Planning, Enterprise licenses). Interface: Browser-based, intuitive for business users, with story builder and Data Explorer.
• Microsoft Power BI: Strengths: Deep integration with Microsoft ecosystem (e.g., Azure, Excel, Teams). Cost-effective, with a free desktop version and affordable Pro licenses. Strong visualization and data modeling (Power Query, DAX). Large community and extensive third-party connectors. Limitations: Limited planning capabilities compared to SAC. Predictive analytics requires integration with Azure Machine Learning. On-premises options (Power BI Report Server) less flexible than cloud. Interface: Desktop and cloud-based, with drag-and-drop visuals and DAX for calculations.
• Tableau: Strengths: Superior visualization with highly customizable dashboards. Broad data connectivity (databases, cloud services, APIs). Strong community and Tableau Public for sharing visualizations. Intuitive drag-and-drop interface for non-technical users. Limitations: No native planning or predictive analytics (requires Tableau AI or third-party tools). Higher licensing costs for enterprise deployments. Less seamless integration with SAP systems compared to SAC. Interface: Desktop and cloud-based (Tableau Cloud), with focus on visual exploration.
• Key Comparison Points: Visualization: All offer rich visuals; Tableau excels in customization, SAC integrates planning visuals, Power BI leverages Microsoft familiarity. Analytics: SAC’s Smart Predict and Smart Insights lead in built-in AI; Power BI and Tableau rely on external AI tools. Integration: SAC dominates SAP environments; Power BI for Microsoft; Tableau for diverse sources. Planning: SAC’s unique strength; Power BI and Tableau focus solely on BI. Cost: Power BI is cost-effective; SAC and Tableau can be pricier for advanced features.
• Applications: SAC: SAP-centric organizations needing BI and planning. Power BI: Microsoft-centric businesses or cost-conscious teams. Tableau: Visualization-focused teams with diverse data sources.
• Challenges: Choosing the right tool based on data environment and budget. Navigating SAC’s SAP-centric design in non-SAP contexts. Assessing trial limitations for full feature comparison.

Hands-On Example:

Scenario: You’re a business analyst comparing SAC, Power BI, and Tableau for your organization’s BI needs. Using the SAC trial, you’ll create a sales dashboard with visualizations, filters, and predictive insights, mimicking a typical Power BI/Tableau workflow, to evaluate SAC’s strengths and limitations.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface and features (from Weeks 1–5).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model.
• Modern browser (e.g., Chrome, Edge) and internet connection.
• Optional: Basic familiarity with Power BI or Tableau (not required, but helpful for context).

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Navigate to “Files” > “Samples” to confirm access to “BestRunJuice_SampleModel.”

Create a Sales Dashboard in SAC (Mimicking Power BI/Tableau):

Navigate to “Create” > “Story” > Select “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Confirm dimensions (e.g., Region, Product, Time) and measures (e.g., Sales Revenue, Quantity Sold).

Build visualizations (comparable to Power BI/Tableau dashboards):

Bar Chart (like Power BI’s clustered column or Tableau’s bar):

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “Sales by Region.”

Customize: Enable data labels, set bar color to blue.

Line Chart (like Power BI’s line chart or Tableau’s trend line):

Add another chart > Select “Line.”

Drag “Sales Revenue” to Y-axis, “Time” (e.g., Month) to X-axis.

Title: “Sales Trend Over Time.”

Table (like Power BI’s table or Tableau’s text table):

Click “Table” in the toolbar.

Add columns: “Product,” “Sales Revenue,” “Quantity Sold.”

Sort “Sales Revenue” in descending order.

Add interactivity (filters, common in Power BI/Tableau):

Click “Filter” > Add a filter for “Region.”

Select “North” and “South” to limit data.

Save the story:

Click “Save” > Name it “Comparison_Story” > Save in “Public” folder.

Test SAC’s Augmented Analytics (Unique Feature):

Open “Comparison_Story.”

Use Smart Insights:

Select the bar chart (“Sales by Region”).

Click “Smart Insights” (lightbulb icon, if available).

Review AI-driven insights (e.g., “North drives 40% of sales due to high Laptop demand”).

Explore Smart Predict:

From “Create” > “Predictive Scenario” > “Time Series Forecasting.”

Select “BestRunJuice_SampleModel” > “Sales Revenue” as the target.

Set “Time” (e.g., Month) as the date dimension.

Run the forecast (default settings).

Save as “Sales_Forecast” in “Public.”

Compare SAC Workflow with Power BI/Tableau:

Reflect on SAC’s dashboard creation:

Visualization: SAC’s drag-and-drop is similar to Power BI/Tableau, but customization (e.g., chart styling) is less flexible than Tableau.

Filters: SAC’s filters are intuitive, like Power BI’s slicers or Tableau’s filter shelves, but SAC’s linked analysis is automatic.

Analytics: SAC’s Smart Insights/Smart Predict are built-in, unlike Power BI’s Azure ML dependency or Tableau’s add-ons.

Interface: SAC’s browser-based interface contrasts with Power BI’s desktop-first approach and Tableau’s hybrid model.

Test SAC’s collaboration:

In “Comparison_Story,” click “Share” > Add a comment: “Review dashboard for BI comparison.”

Note sharing options (e.g., public link, user-specific sharing, if available in trial).

Validate and Troubleshoot:

Validation:

Confirm dashboard: “Comparison_Story” includes bar chart, line chart, table, and region filter (North, South).

Verify analytics: Smart Insights provides insights; “Sales_Forecast” generated (or noted as restricted).

Check interactivity: Filters update all visuals dynamically.

Troubleshooting:

Feature Restrictions: Trial may limit predictive or sharing features; note for Enterprise licenses.

Interpretation: This hands-on example compares SAC with Power BI and Tableau by creating a dashboard in the trial environment, testing visualizations, filters, and predictive analytics. By replicating a typical BI workflow, you gain insight into SAC’s strengths (unified BI/planning, AI) and limitations (less visualization flexibility), preparing for Week 7’s focus on SAP Cloud Platform integration.

Supplemental Information: SAC vs. Competitors: https://www.sap.com/products/technology-platform/analytics-cloud/compare.html. Power BI Overview: https://powerbi.microsoft.com/en-us/. Tableau Overview: https://www.tableau.com/. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud.

Discussion Points:

• How does SAC’s unified BI and planning compare to Power BI/Tableau’s BI focus?
• What advantages does SAC’s SAP integration offer in SAP-centric organizations?
• How do SAC’s augmented analytics (Smart Insights, Smart Predict) impact its competitive edge?
• What visualization customization trade-offs did you notice in SAC vs. Tableau?
• How might licensing costs influence the choice between SAC, Power BI, and Tableau?

Week 7: SAP Cloud Platform Integration

Introduction: SAP Analytics Cloud (SAC) excels in integrating with SAP systems through the SAP Business Technology Platform (BTP), enabling seamless data connectivity and analytics. This week focuses on understanding SAC’s integration with SAP Cloud Platform (now part of BTP), including connectivity to SAP data sources like S/4HANA, BW/4HANA, and HANA. The emphasis is on practical usage, guiding you through connecting to a sample SAP data source in the SAC trial environment and creating a visualization to explore integration capabilities.

Learning Objectives: By the end of this week, you will be able to:

• Understand SAC’s integration with SAP Business Technology Platform (BTP).
• Identify supported SAP data sources (e.g., S/4HANA, BW/4HANA, HANA).
• Explore live and import data connections in SAC.
• Connect to a sample SAP data source and create a visualization in the trial.
• Troubleshoot integration issues in the trial environment.

Scope: This week covers SAC’s integration with SAP Cloud Platform, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, and Week 6’s comparison with other BI tools. It prepares for Week 8’s focus on creating stories by demonstrating how SAC leverages SAP data for analytics.

Background Information: SAC’s integration with SAP Cloud Platform (BTP) enables robust data connectivity and analytics:

• SAP Business Technology Platform (BTP): A cloud platform providing integration, extension, and data management services. SAC is built on BTP, leveraging its services for connectivity and scalability. Key components: SAP HANA Cloud, SAP Integration Suite, and SAP Data Warehouse Cloud.
• Supported SAP Data Sources: SAP S/4HANA: ERP system for real-time business processes. SAP BW/4HANA: Data warehouse for analytics and reporting. SAP HANA: In-memory database for high-performance analytics. SAP SuccessFactors: HR and workforce data. SAP Ariba: Procurement and supply chain data.
• Connection Types: Live Connections: Real-time access to SAP data without replication (e.g., HANA, BW/4HANA). Import Connections: Data copied to SAC’s HANA Cloud (e.g., CSV, Excel, or SAP extracts).
• Integration Features: SAP Integration Suite: Connects SAP and non-SAP systems via APIs, OData, or JDBC. Prebuilt Content: Templates for SAP systems (e.g., S/4HANA finance dashboards). Single Sign-On (SSO): Unified authentication across SAP systems.
• Applications: Real-time sales dashboards from S/4HANA data. Financial planning using BW/4HANA actuals. Workforce analytics from SuccessFactors.
• Challenges: Trial environment may limit live connections to SAP systems. Configuring secure connections (e.g., SSO, VPN) in production. Ensuring data consistency across live and import connections.

Hands-On Example:

Scenario: You’re a business analyst evaluating SAC’s integration with SAP systems for your organization. Using the SAC trial, you’ll connect to a sample SAP data source (or simulate integration with a sample model), create a visualization, and explore connectivity options to understand SAC’s integration capabilities.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface and features (from Weeks 1–6).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” (simulating SAP data) or equivalent sales model.
• Modern browser (e.g., Chrome, Edge) and internet connection.
• Note: Trial may restrict live connections to SAP systems; sample models simulate integration.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Navigate to “Files” > “Samples” to confirm access to “BestRunJuice_SampleModel” (simulating SAP data, e.g., S/4HANA sales).

Troubleshooting:

If login fails, reset your password via the SAP trial portal.

Clear browser cache if the interface doesn’t load.

Explore Data Connections:

Check available connections:

Navigate to “Browse” > “Connections” (if accessible in trial).

Observe sample connections (e.g., “SAP HANA,” “SAP BW,” or “File Server” for imports).

Note: Trial may limit live connections; “BestRunJuice_SampleModel” uses an import connection to simulate SAP data.

Create a model to explore integration:

From “Create” > “Model.”

Select “Use a datasource” > “Import Data” > Choose “BestRunJuice_SampleModel.”

Review the model wizard:

Confirm dimensions (e.g., Region, Product, Time) and measures (e.g., Sales Revenue).

Note the import connection (data copied to SAC’s HANA Cloud).

Save as “SAP_Sales_Model” in “Public.”

Simulate a live connection (if available):

In the model wizard, select “Live Data Connection” (if enabled).

Observe options like “SAP HANA” or “SAP BW” (trial may restrict access).

Note the real-time access concept for SAP systems.

Verify: Model created; import connection simulates SAP data integration.

Expected Outcome: Understanding of import vs. live connections in SAC’s integration architecture.

Troubleshooting:

If “Connections” is restricted, rely on sample model behavior.

Use another sample dataset if “BestRunJuice_SampleModel” is unavailable.

Create a Story with SAP Data:

From “Create” > “Story” > Select “Canvas” mode.

Add the “SAP_Sales_Model” as the data source:

Click “Add Data” > “Data from a Model” > Select “SAP_Sales_Model.”

Build visualizations:

Bar Chart:

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “SAP Sales by Region.”

Customize: Enable data labels, set bar color to green.

KPI Tile:

Click “Text” or “KPI” > Add a KPI for total “Sales Revenue.”

Title: “Total Sales.”

Add a filter:

Click “Filter” > Select “Time” > Choose the most recent year (e.g., 2024).

Verify charts update to reflect filtered data.

Save the story:

Click “Save” > Name it “SAP_Integration_Story” > Save in “Public.”

Explore Prebuilt Content (Simulating SAP Integration):

Navigate to “Files” > “Samples.”

Open a sample story or model related to SAP systems (e.g., “SAP S/4HANA Sales” or “Financials”).

Explore the content:

Observe prebuilt dashboards with SAP-specific metrics (e.g., revenue, profit).

Note any live connection indicators (e.g., “SAP HANA” in data source details).

Interact with filters or drill-downs to simulate real-time SAP data access.

Verify: Sample content demonstrates SAC’s SAP integration capabilities.

Expected Outcome: Insight into how SAC leverages prebuilt SAP content for analytics.

Troubleshooting:

If SAP-specific samples are unavailable, use “BestRunJuice_SampleModel” stories.

Note trial restrictions on live connections.

Validate and Troubleshoot:

Validation:

Confirm model: “SAP_Sales_Model” created with correct dimensions and measures.

Verify story: “SAP_Integration_Story” includes a bar chart and KPI tile, filtered by year.

Check connections: Import connection used; live connection options noted (if available).

Ensure sample SAP content explored, highlighting integration features.

Test interactivity: Filters update visuals dynamically.

Troubleshooting:

Connection Issues: Verify sample model; live connections may be trial-restricted.

Story Errors: Ensure “SAP_Sales_Model” is linked; reselect if visuals fail.

Sample Content: Use alternative samples if SAP-specific content is missing.

Performance: Refresh browser if SAC lags; check internet connection.

Support: Use SAP Community (https://community.sap.com/topics/analytics-cloud) or trial help portal.

Clean Up:

Save “SAP_Sales_Model” and “SAP_Integration_Story” in “Public.”

Log out of SAC via the user profile menu (top-right).

Keep the trial account active for subsequent weeks (valid for 30 days).

Interpretation: This hands-on example provides practical experience with SAC’s SAP Cloud Platform integration by connecting to a sample data source and creating a visualization in the trial environment. By exploring import connections and sample SAP content, you gain insight into SAC’s seamless integration with SAP systems, preparing for Week 8’s focus on creating stories.

Supplemental Information: SAC Integration Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP BTP Overview: https://www.sap.com/products/business-technology-platform.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud.

Discussion Points:

• How does SAC’s BTP integration enhance SAP system connectivity?
• What are the benefits of live vs. import connections for SAP data?
• How do prebuilt SAP templates streamline analytics workflows?
• What challenges might arise when integrating SAC with non-SAP systems?
• How does SAC’s integration compare to Power BI’s Microsoft ecosystem connectivity?

Week 8: Creating Your First Story in SAC

Introduction: Stories in SAP Analytics Cloud (SAC) are interactive dashboards that combine visualizations, tables, and filters to present data insights effectively. This week focuses on creating your first comprehensive story in SAC, leveraging its story builder to design a dashboard with charts, calculations, and interactivity. The emphasis is on practical usage, guiding you through building a sales-focused story in the SAC trial environment to master storytelling techniques.

Learning Objectives: By the end of this week, you will be able to:

• Understand the purpose and structure of stories in SAC.
• Create a story with multiple visualizations (charts, tables) and filters.
• Add calculated measures and input controls for interactivity.
• Organize and save a story in the SAC file structure.
• Troubleshoot story creation issues in the trial environment.

Scope: This week covers creating a story in SAC, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, and Week 7’s SAP Cloud Platform integration. It prepares for Week 9’s security and data privacy overview by ensuring proficiency in SAC’s core storytelling functionality.

Background Information: Stories are SAC’s primary method for presenting data insights:

• Story Components: Visualizations: Charts (bar, line, pie), tables, and KPIs to display data. Filters: Interactive controls to slice data (e.g., by region, time). Calculated Measures: Custom metrics created via formulas (e.g., profit margin). Input Controls: Dynamic filters for users to adjust data views. Layouts: Canvas (free-form), responsive (mobile-friendly), or grid modes.
• Key Features: Drag-and-drop interface for building visuals. Linked analysis to sync filters across visuals. Collaboration tools (comments, sharing) for team feedback. Smart features (e.g., Smart Insights) for AI-driven analysis.
• Applications: Sales performance dashboards for executives. Financial reports with interactive filters. Operational analytics with real-time data views.
• Challenges: Managing complex stories with multiple visuals. Optimizing performance for large datasets. Navigating trial limitations (e.g., restricted data sources or features).

Hands-On Example:

Scenario: You’re a business analyst tasked with creating a sales dashboard in SAC to present regional sales performance to stakeholders. Using the SAC trial, you’ll build a story with visualizations, filters, calculated measures, and input controls, simulating a real-world analytics task.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface and features (from Weeks 1–7).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model.
• Modern browser (e.g., Chrome, Edge) and internet connection.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Create a New Story:

From the home page, click “Create” > “Story” > Select “Canvas” mode for free-form layout.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Confirm dimensions (e.g., Region, Product, Time) and measures (e.g., Sales Revenue, Quantity Sold).

Set up the story:

Add a title: Click “Text” in the toolbar, enter “Regional Sales Dashboard.”

Adjust font size to 20pt and align center.

Add Visualizations:

Bar Chart:

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “Sales by Region.”

Customize: Enable data labels, set bar color to blue.

Pie Chart:

Add another chart > Select “Pie.”

Drag “Sales Revenue” to Measures, “Product” to Color.

Title: “Sales by Product.”

Table:

Click “Table” in the toolbar.

Add columns: “Region,” “Product,” “Sales Revenue,” “Quantity Sold.”

Sort “Sales Revenue” in descending order.

KPI Tile:

Click “Text” or “KPI” > Add a KPI for total “Sales Revenue.”

Title: “Total Sales.”

Add Calculated Measures:

Create a profit margin calculation:

In the story, click “Data” view > “Add” > “Calculation.”

Select “Calculated Measure.”

Name: “Profit Margin.”

Formula: ([Sales Revenue] - [Cost]) / [Sales Revenue] * 100 (use actual measure names from the model).

Format as percentage.

Add Filters and Input Controls:

Add a page filter:

Click “Filter” > Select “Time.”

Choose the most recent year (e.g., 2024).

Add an input control:

Click “Input Control” > Select “Region.”

Test by selecting a region; confirm visuals update.

Test Collaboration Features:

Add a comment and share the story.

Save and Organize the Story:

Save as “First_Sales_Story” in a new folder.

Validate and Troubleshoot:

Validation:

Confirm story functionality.

Troubleshooting:

Address common issues.

Interpretation: This hands-on example builds proficiency in creating a comprehensive story in SAC, combining visualizations, calculations, and interactivity in the trial environment. By designing a sales dashboard, you master SAC’s storytelling capabilities, preparing for Week 9’s focus on security and data privacy.

Supplemental Information: SAC Story Building Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud. SAC Tutorials: https://www.sap.com/products/technology-platform/analytics-cloud/resources.html.

Discussion Points:

• How does SAC’s story builder support effective data storytelling?
• What are the benefits of calculated measures for custom analytics?
• How do filters and input controls enhance stakeholder engagement?
• What challenges might arise when building complex stories in SAC?
• How does SAC’s storytelling compare to dashboards in Power BI or Tableau?

Week 9: Security and Data Privacy Overview

Introduction: Security and data privacy are critical for ensuring safe and compliant use of SAP Analytics Cloud (SAC). This week focuses on understanding SAC’s security framework, including user roles, permissions, data access controls, and compliance with privacy regulations. The emphasis is on practical usage, guiding you through exploring security settings and role-based access in the SAC trial environment to understand how SAC protects data and users.

Learning Objectives: By the end of this week, you will be able to:

• Describe SAC’s security and data privacy features.
• Understand user roles, permissions, and data access controls.
• Explore security settings and role assignments in the SAC trial.
• Identify how SAC ensures compliance with privacy regulations (e.g., GDPR, CCPA).
• Troubleshoot security-related issues in the trial environment.

Scope: This week covers SAC’s security and data privacy framework, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, Week 7’s SAP Cloud Platform integration, and Week 8’s story creation. It prepares for Week 10’s exploration of use cases across industries by ensuring an understanding of SAC’s secure environment.

Background Information: SAC’s security and data privacy features safeguard sensitive data and ensure compliance:

• Security Features: User Authentication: Single Sign-On (SSO) via SAML 2.0 or SAP Identity Authentication Service. Role-Based Access Control (RBAC): Granular permissions for users (e.g., Viewer, BI Content Creator, Planning Modeler). Data Access Controls: Restrict access to models, stories, or dimensions (e.g., region-specific data). Encryption: Data encrypted in transit (TLS) and at rest (AES-256). Audit Logging: Tracks user actions for compliance and monitoring.
• Data Privacy Compliance: Supports regulations like GDPR (EU), CCPA (California), and others. Features: Data anonymization, consent management, and data residency options. SAP’s data centers (e.g., US, EU) comply with regional privacy laws.
• Key Components: Users: Individual accounts with assigned roles. Roles: Define permissions (e.g., view, edit, share). Teams: Group users for easier permission management. Folders: Control access to content (e.g., Public, private folders).
• Applications: Restrict sales data access to regional managers. Ensure GDPR-compliant handling of customer data. Audit user activity for regulatory reporting.
• Challenges: Trial environment may limit access to advanced security settings (e.g., SSO, team management). Configuring granular data access for large organizations. Balancing security with user accessibility.

Hands-On Example:

Scenario: You’re a business analyst tasked with evaluating SAC’s security features for your organization. Using the SAC trial, you’ll explore user roles, permissions, and data access controls by creating a story, assigning access, and reviewing security settings to understand SAC’s secure environment.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface and story creation (from Weeks 1–8).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model.
• Modern browser (e.g., Chrome, Edge) and internet connection.
• Note: Trial may restrict advanced security features (e.g., multi-user management, SSO); focus on available settings.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Create a Story to Test Security:

From “Create” > “Story” > Select “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Add a visualization:

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “Secure Sales by Region.”

Enable data labels, set color to green.

Add a filter:

Click “Filter” > Select “Region” > Choose “North.”

Save the story:

Click “Save” > Name it “Secure_Sales_Story” > Save in “Public” folder.

Explore Security Settings:

Check user role:

Click the user profile (top-right) > “System” > “About.”

Note your user ID and role (trial typically assigns an admin-like role with BI and planning access).

Navigate to “Security” (if accessible):

Go to “Browse” > “Security” > “Roles.”

Observe predefined roles (e.g., BI Content Creator, Planning Modeler) and permissions.

Test Folder Permissions:

Create a private folder:

Navigate to “Files” > “Public.”

Click “New Folder” > Name it “Secure_Week9.”

Move “Secure_Sales_Story” to “Secure_Week9.”

Set folder permissions (if available).

Explore Data Access Controls:

Open “Secure_Sales_Story.”

Add a data access restriction (if available).

Simulate data access with a second story.

Review Audit and Compliance Features:

Check audit logs (if accessible).

Explore compliance settings.

Validate and Troubleshoot:

Validation:

Confirm story creation.

Troubleshooting:

Address common issues.

Interpretation: This hands-on example builds proficiency in SAC’s security and data privacy features by exploring roles, permissions, and data access controls in the trial environment. By creating stories and managing access, you gain practical insight into SAC’s secure framework, preparing for Week 10’s exploration of industry use cases.

Supplemental Information: SAC Security Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP BTP Security: https://www.sap.com/products/business-technology-platform/security.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud.

Discussion Points:

• How does SAC’s role-based access control support organizational security?
• What are the benefits of data access controls for sensitive data?
• How does SAC’s encryption ensure data privacy compliance?
• What challenges might arise when configuring security in a trial vs. production?
• How do SAC’s security features compare to Power BI or Tableau?

Week 10: Use Cases Across Industries

Introduction: SAP Analytics Cloud (SAC) is a versatile platform that supports a wide range of industry-specific use cases, from retail to finance to manufacturing. This final week explores how SAC’s business intelligence (BI), planning, and predictive analytics capabilities address real-world challenges across industries. The emphasis is on practical usage, guiding you through creating an industry-specific story in the SAC trial environment to simulate a retail sales use case, consolidating skills learned throughout the course.

Learning Objectives: By the end of this week, you will be able to:

• Identify key SAC use cases across industries (e.g., retail, finance, manufacturing).
• Understand how SAC’s features (BI, planning, predictive) solve industry challenges.
• Create an industry-specific story in SAC with visualizations and interactivity.
• Apply course concepts (e.g., security, integration) to a practical use case.
• Reflect on SAC’s value for industry applications.

Scope: This week covers SAC use cases across industries, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, Week 7’s SAP Cloud Platform integration, Week 8’s story creation, and Week 9’s security and data privacy. It concludes Course 1 by demonstrating SAC’s practical applications.

Background Information: SAC’s unified platform supports diverse industry needs:

• Retail: Use Case: Sales performance tracking and demand forecasting. Features: Dashboards for sales by region/product, predictive analytics for inventory planning. Example: Visualize sales trends, forecast demand using Smart Predict.
• Finance: Use Case: Budget planning and financial reporting. Features: Collaborative planning models, real-time reporting from S/4HANA. Example: Create budgets, track actuals vs. forecasts.
• Manufacturing: Use Case: Supply chain optimization and production analytics. Features: Real-time KPIs, predictive maintenance insights. Example: Monitor production efficiency, predict equipment failures.
• Healthcare: Use Case: Patient care analytics and resource planning. Features: Dashboards for patient outcomes, planning for staff allocation. Example: Analyze bed occupancy, plan staffing needs.
• Public Sector: Use Case: Budget allocation and program performance. Features: Secure reporting, planning for public funds. Example: Track program spending, ensure compliance.
• Key Benefits: Unified BI, planning, and predictive analytics reduce tool fragmentation. Native SAP integration (e.g., S/4HANA, BW/4HANA) for seamless data flows. Secure, compliant environment (GDPR, CCPA) for sensitive data.
• Challenges: Tailoring SAC to non-SAP data environments. Managing costs for large-scale industry deployments. Trial limitations may restrict advanced features (e.g., live connections).

Hands-On Example:

Scenario: You’re a business analyst for a retail company using SAC to track and analyze sales performance. Using the SAC trial, you’ll create a retail sales story with visualizations, filters, and predictive insights, simulating a real-world retail use case while applying security and integration concepts from prior weeks.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface, story creation, security, and integration (from Weeks 1–9).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model (simulating retail data).
• Modern browser (e.g., Chrome, Edge) and internet connection.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Create a Retail Sales Story:

From “Create” > “Story” > Select “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Confirm dimensions (e.g., Region, Product, Time, Store) and measures (e.g., Sales Revenue, Quantity Sold).

Set up the story:

Add a title: Click “Text” in the toolbar, enter “Retail Sales Dashboard.”

Set font size to 20pt, align center.

Add Visualizations (Retail Focus):

Bar Chart (Sales by Region):

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “Sales by Region.”

Customize: Enable data labels, set color to blue.

Geo Map (Sales by Store Location):

Click “Chart” > “Geo Map” (if available; else use a pie chart).

Drag “Sales Revenue” to Size, “Store” or “Region” to Location.

Title: “Sales by Store.”

Customize: Adjust map zoom, use gradient colors.

Table (Product Performance):

Click “Table” in the toolbar.

Add columns: “Product,” “Sales Revenue,” “Quantity Sold.”

Sort “Sales Revenue” in descending order.

Title: “Product Performance.”

KPI Tile (Total Sales):

Click “Text” or “KPI” > Add a KPI for total “Sales Revenue.”

Title: “Total Retail Sales.”

Customize: Set font size to 16pt, bold.

Arrange visuals:

Drag and resize for a clean layout (e.g., bar chart top-left, geo map top-right, table bottom-left, KPI bottom-right).

Add Filters and Input Controls:

Add a page filter:

Click “Filter” > Select “Time.”

Choose the most recent year (e.g., 2024).

Add an input control:

Click “Input Control” > Select “Product.”

Test by selecting a product; confirm visuals update.

Incorporate Predictive Analytics (Demand Forecasting):

Open the story.

Use Smart Insights:

Select the bar chart (“Sales by Region”).

Click “Smart Insights” (lightbulb icon, if available).

Create a predictive forecast:

From “Create” > “Predictive Scenario” > “Time Series Forecasting.”

Select “BestRunJuice_SampleModel” > “Sales Revenue” as the target.

Set “Time” (e.g., Month) as the date dimension.

Apply Security and Integration Concepts:

Secure the story in a folder.

Simulate SAP integration.

Validate and Troubleshoot:

Validation:

Confirm story functionality.

Troubleshooting:

Address common issues.

Interpretation: This hands-on example builds proficiency in creating a comprehensive story in SAC, combining visualizations, calculations, and interactivity in the trial environment. By designing a sales dashboard, you master SAC’s storytelling capabilities, preparing for Week 9’s focus on security and data privacy.

Supplemental Information: SAC Story Building Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud. SAC Tutorials: https://www.sap.com/products/technology-platform/analytics-cloud/resources.html.

Discussion Points:

• How does SAC’s story builder support effective data storytelling?
• What are the benefits of calculated measures for custom analytics?
• How do filters and input controls enhance stakeholder engagement?
• What challenges might arise when building complex stories in SAC?
• How does SAC’s storytelling compare to dashboards in Power BI or Tableau?

Week 9: Security and Data Privacy Overview

Introduction: Security and data privacy are critical for ensuring safe and compliant use of SAP Analytics Cloud (SAC). This week focuses on understanding SAC’s security framework, including user roles, permissions, data access controls, and compliance with privacy regulations. The emphasis is on practical usage, guiding you through exploring security settings and role-based access in the SAC trial environment to understand how SAC protects data and users.

Learning Objectives: By the end of this week, you will be able to:

• Describe SAC’s security and data privacy features.
• Understand user roles, permissions, and data access controls.
• Explore security settings and role assignments in the SAC trial.
• Identify how SAC ensures compliance with privacy regulations (e.g., GDPR, CCPA).
• Troubleshoot security-related issues in the trial environment.

Scope: This week covers SAC’s security and data privacy framework, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, Week 7’s SAP Cloud Platform integration, and Week 8’s story creation. It prepares for Week 10’s exploration of use cases across industries by ensuring an understanding of SAC’s secure environment.

Background Information: SAC’s security and data privacy features safeguard sensitive data and ensure compliance:

• Security Features: User Authentication: Single Sign-On (SSO) via SAML 2.0 or SAP Identity Authentication Service. Role-Based Access Control (RBAC): Granular permissions for users (e.g., Viewer, BI Content Creator, Planning Modeler). Data Access Controls: Restrict access to models, stories, or dimensions (e.g., region-specific data). Encryption: Data encrypted in transit (TLS) and at rest (AES-256). Audit Logging: Tracks user actions for compliance and monitoring.
• Data Privacy Compliance: Supports regulations like GDPR (EU), CCPA (California), and others. Features: Data anonymization, consent management, and data residency options. SAP’s data centers (e.g., US, EU) comply with regional privacy laws.
• Key Components: Users: Individual accounts with assigned roles. Roles: Define permissions (e.g., view, edit, share). Teams: Group users for easier permission management. Folders: Control access to content (e.g., Public, private folders).
• Applications: Restrict sales data access to regional managers. Ensure GDPR-compliant handling of customer data. Audit user activity for regulatory reporting.
• Challenges: Trial environment may limit access to advanced security settings (e.g., SSO, team management). Configuring granular data access for large organizations. Balancing security with user accessibility.

Hands-On Example:

Scenario: You’re a business analyst tasked with evaluating SAC’s security features for your organization. Using the SAC trial, you’ll explore user roles, permissions, and data access controls by creating a story, assigning access, and reviewing security settings to understand SAC’s secure environment.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface and story creation (from Weeks 1–8).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model.
• Modern browser (e.g., Chrome, Edge) and internet connection.
• Note: Trial may restrict advanced security features (e.g., multi-user management, SSO); focus on available settings.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Create a Story to Test Security:

From “Create” > “Story” > Select “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Add a visualization:

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “Secure Sales by Region.”

Enable data labels, set color to green.

Add a filter:

Click “Filter” > Select “Region” > Choose “North.”

Save the story:

Click “Save” > Name it “Secure_Sales_Story” > Save in “Public” folder.

Explore Security Settings:

Check user role:

Click the user profile (top-right) > “System” > “About.”

Note your user ID and role (trial typically assigns an admin-like role with BI and planning access).

Navigate to “Security” (if accessible):

Go to “Browse” > “Security” > “Roles.”

Observe predefined roles (e.g., BI Content Creator, Planning Modeler) and permissions.

Test Folder Permissions:

Create a private folder:

Navigate to “Files” > “Public.”

Click “New Folder” > Name it “Secure_Week9.”

Move “Secure_Sales_Story” to “Secure_Week9.”

Set folder permissions (if available).

Explore Data Access Controls:

Open “Secure_Sales_Story.”

Add a data access restriction (if available).

Simulate data access with a second story.

Review Audit and Compliance Features:

Check audit logs (if accessible).

Explore compliance settings.

Validate and Troubleshoot:

Validation:

Confirm story creation.

Troubleshooting:

Address common issues.

Interpretation: This hands-on example builds proficiency in SAC’s security and data privacy features by exploring roles, permissions, and data access controls in the trial environment. By creating stories and managing access, you gain practical insight into SAC’s secure framework, preparing for Week 10’s exploration of industry use cases.

Supplemental Information: SAC Security Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP BTP Security: https://www.sap.com/products/business-technology-platform/security.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud.

Discussion Points:

• How does SAC’s role-based access control support organizational security?
• What are the benefits of data access controls for sensitive data?
• How does SAC’s encryption ensure data privacy compliance?
• What challenges might arise when configuring security in a trial vs. production?
• How do SAC’s security features compare to Power BI or Tableau?

Week 10: Use Cases Across Industries

Introduction: SAP Analytics Cloud (SAC) is a versatile platform that supports a wide range of industry-specific use cases, from retail to finance to manufacturing. This final week explores how SAC’s business intelligence (BI), planning, and predictive analytics capabilities address real-world challenges across industries. The emphasis is on practical usage, guiding you through creating an industry-specific story in the SAC trial environment to simulate a retail sales use case, consolidating skills learned throughout the course.

Learning Objectives: By the end of this week, you will be able to:

• Identify key SAC use cases across industries (e.g., retail, finance, manufacturing).
• Understand how SAC’s features (BI, planning, predictive) solve industry challenges.
• Create an industry-specific story in SAC with visualizations and interactivity.
• Apply course concepts (e.g., security, integration) to a practical use case.
• Reflect on SAC’s value for industry applications.

Scope: This week covers SAC use cases across industries, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, Week 7’s SAP Cloud Platform integration, Week 8’s story creation, and Week 9’s security and data privacy. It concludes Course 1 by demonstrating SAC’s practical applications.

Background Information: SAC’s unified platform supports diverse industry needs:

• Retail: Use Case: Sales performance tracking and demand forecasting. Features: Dashboards for sales by region/product, predictive analytics for inventory planning. Example: Visualize sales trends, forecast demand using Smart Predict.
• Finance: Use Case: Budget planning and financial reporting. Features: Collaborative planning models, real-time reporting from S/4HANA. Example: Create budgets, track actuals vs. forecasts.
• Manufacturing: Use Case: Supply chain optimization and production analytics. Features: Real-time KPIs, predictive maintenance insights. Example: Monitor production efficiency, predict equipment failures.
• Healthcare: Use Case: Patient care analytics and resource planning. Features: Dashboards for patient outcomes, planning for staff allocation. Example: Analyze bed occupancy, plan staffing needs.
• Public Sector: Use Case: Budget allocation and program performance. Features: Secure reporting, planning for public funds. Example: Track program spending, ensure compliance.
• Key Benefits: Unified BI, planning, and predictive analytics reduce tool fragmentation. Native SAP integration (e.g., S/4HANA, BW/4HANA) for seamless data flows. Secure, compliant environment (GDPR, CCPA) for sensitive data.
• Challenges: Tailoring SAC to non-SAP data environments. Managing costs for large-scale industry deployments. Trial limitations may restrict advanced features (e.g., live connections).

Hands-On Example:

Scenario: You’re a business analyst for a retail company using SAC to track and analyze sales performance. Using the SAC trial, you’ll create a retail sales story with visualizations, filters, and predictive insights, simulating a real-world retail use case while applying security and integration concepts from prior weeks.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface, story creation, security, and integration (from Weeks 1–9).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model (simulating retail data).
• Modern browser (e.g., Chrome, Edge) and internet connection.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Create a Retail Sales Story:

From “Create” > “Story” > Select “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Confirm dimensions (e.g., Region, Product, Time, Store) and measures (e.g., Sales Revenue, Quantity Sold).

Set up the story:

Add a title: Click “Text” in the toolbar, enter “Retail Sales Dashboard.”

Set font size to 20pt, align center.

Add Visualizations (Retail Focus):

Bar Chart (Sales by Region):

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “Sales by Region.”

Customize: Enable data labels, set color to blue.

Geo Map (Sales by Store Location):

Click “Chart” > “Geo Map” (if available; else use a pie chart).

Drag “Sales Revenue” to Size, “Store” or “Region” to Location.

Title: “Sales by Store.”

Customize: Adjust map zoom, use gradient colors.

Table (Product Performance):

Click “Table” in the toolbar.

Add columns: “Product,” “Sales Revenue,” “Quantity Sold.”

Sort “Sales Revenue” in descending order.

Title: “Product Performance.”

KPI Tile (Total Sales):

Click “Text” or “KPI” > Add a KPI for total “Sales Revenue.”

Title: “Total Retail Sales.”

Customize: Set font size to 16pt, bold.

Arrange visuals:

Drag and resize for a clean layout (e.g., bar chart top-left, geo map top-right, table bottom-left, KPI bottom-right).

Add Filters and Input Controls:

Add a page filter:

Click “Filter” > Select “Time.”

Choose the most recent year (e.g., 2024).

Add an input control:

Click “Input Control” > Select “Product.”

Test by selecting a product; confirm visuals update.

Incorporate Predictive Analytics (Demand Forecasting):

Open the story.

Use Smart Insights:

Select the bar chart (“Sales by Region”).

Click “Smart Insights” (lightbulb icon, if available).

Create a predictive forecast:

From “Create” > “Predictive Scenario” > “Time Series Forecasting.”

Select “BestRunJuice_SampleModel” > “Sales Revenue” as the target.

Set “Time” (e.g., Month) as the date dimension.

Apply Security and Integration Concepts:

Secure the story in a folder.

Simulate SAP integration.

Validate and Troubleshoot:

Validation:

Confirm story functionality.

Troubleshooting:

Address common issues.

Interpretation: This hands-on example builds proficiency in creating a comprehensive story in SAC, combining visualizations, calculations, and interactivity in the trial environment. By designing a sales dashboard, you master SAC’s storytelling capabilities, preparing for Week 9’s focus on security and data privacy.

Supplemental Information: SAC Story Building Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud. SAC Tutorials: https://www.sap.com/products/technology-platform/analytics-cloud/resources.html.

Discussion Points:

• How does SAC’s story builder support effective data storytelling?
• What are the benefits of calculated measures for custom analytics?
• How do filters and input controls enhance stakeholder engagement?
• What challenges might arise when building complex stories in SAC?
• How does SAC’s storytelling compare to dashboards in Power BI or Tableau?

Week 9: Security and Data Privacy Overview

Introduction: Security and data privacy are critical for ensuring safe and compliant use of SAP Analytics Cloud (SAC). This week focuses on understanding SAC’s security framework, including user roles, permissions, data access controls, and compliance with privacy regulations. The emphasis is on practical usage, guiding you through exploring security settings and role-based access in the SAC trial environment to understand how SAC protects data and users.

Learning Objectives: By the end of this week, you will be able to:

• Describe SAC’s security and data privacy features.
• Understand user roles, permissions, and data access controls.
• Explore security settings and role assignments in the SAC trial.
• Identify how SAC ensures compliance with privacy regulations (e.g., GDPR, CCPA).
• Troubleshoot security-related issues in the trial environment.

Scope: This week covers SAC’s security and data privacy framework, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, Week 7’s SAP Cloud Platform integration, and Week 8’s story creation. It prepares for Week 10’s exploration of use cases across industries by ensuring an understanding of SAC’s secure environment.

Background Information: SAC’s security and data privacy features safeguard sensitive data and ensure compliance:

• Security Features: User Authentication: Single Sign-On (SSO) via SAML 2.0 or SAP Identity Authentication Service. Role-Based Access Control (RBAC): Granular permissions for users (e.g., Viewer, BI Content Creator, Planning Modeler). Data Access Controls: Restrict access to models, stories, or dimensions (e.g., region-specific data). Encryption: Data encrypted in transit (TLS) and at rest (AES-256). Audit Logging: Tracks user actions for compliance and monitoring.
• Data Privacy Compliance: Supports regulations like GDPR (EU), CCPA (California), and others. Features: Data anonymization, consent management, and data residency options. SAP’s data centers (e.g., US, EU) comply with regional privacy laws.
• Key Components: Users: Individual accounts with assigned roles. Roles: Define permissions (e.g., view, edit, share). Teams: Group users for easier permission management. Folders: Control access to content (e.g., Public, private folders).
• Applications: Restrict sales data access to regional managers. Ensure GDPR-compliant handling of customer data. Audit user activity for regulatory reporting.
• Challenges: Trial environment may limit access to advanced security settings (e.g., SSO, team management). Configuring granular data access for large organizations. Balancing security with user accessibility.

Hands-On Example:

Scenario: You’re a business analyst tasked with evaluating SAC’s security features for your organization. Using the SAC trial, you’ll explore user roles, permissions, and data access controls by creating a story, assigning access, and reviewing security settings to understand SAC’s secure environment.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface and story creation (from Weeks 1–8).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model.
• Modern browser (e.g., Chrome, Edge) and internet connection.
• Note: Trial may restrict advanced security features (e.g., multi-user management, SSO); focus on available settings.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Create a Story to Test Security:

From “Create” > “Story” > Select “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Add a visualization:

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “Secure Sales by Region.”

Enable data labels, set color to green.

Add a filter:

Click “Filter” > Select “Region” > Choose “North.”

Save the story:

Click “Save” > Name it “Secure_Sales_Story” > Save in “Public” folder.

Explore Security Settings:

Check user role:

Click the user profile (top-right) > “System” > “About.”

Note your user ID and role (trial typically assigns an admin-like role with BI and planning access).

Navigate to “Security” (if accessible):

Go to “Browse” > “Security” > “Roles.”

Observe predefined roles (e.g., BI Content Creator, Planning Modeler) and permissions.

Test Folder Permissions:

Create a private folder:

Navigate to “Files” > “Public.”

Click “New Folder” > Name it “Secure_Week9.”

Move “Secure_Sales_Story” to “Secure_Week9.”

Set folder permissions (if available).

Explore Data Access Controls:

Open “Secure_Sales_Story.”

Add a data access restriction (if available).

Simulate data access with a second story.

Review Audit and Compliance Features:

Check audit logs (if accessible).

Explore compliance settings.

Validate and Troubleshoot:

Validation:

Confirm story creation.

Troubleshooting:

Address common issues.

Interpretation: This hands-on example builds proficiency in SAC’s security and data privacy features by exploring roles, permissions, and data access controls in the trial environment. By creating stories and managing access, you gain practical insight into SAC’s secure framework, preparing for Week 10’s exploration of industry use cases.

Supplemental Information: SAC Security Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP BTP Security: https://www.sap.com/products/business-technology-platform/security.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud.

Discussion Points:

• How does SAC’s role-based access control support organizational security?
• What are the benefits of data access controls for sensitive data?
• How does SAC’s encryption ensure data privacy compliance?
• What challenges might arise when configuring security in a trial vs. production?
• How do SAC’s security features compare to Power BI or Tableau?

Week 10: Use Cases Across Industries

Introduction: SAP Analytics Cloud (SAC) is a versatile platform that supports a wide range of industry-specific use cases, from retail to finance to manufacturing. This final week explores how SAC’s business intelligence (BI), planning, and predictive analytics capabilities address real-world challenges across industries. The emphasis is on practical usage, guiding you through creating an industry-specific story in the SAC trial environment to simulate a retail sales use case, consolidating skills learned throughout the course.

Learning Objectives: By the end of this week, you will be able to:

• Identify key SAC use cases across industries (e.g., retail, finance, manufacturing).
• Understand how SAC’s features (BI, planning, predictive) solve industry challenges.
• Create an industry-specific story in SAC with visualizations and interactivity.
• Apply course concepts (e.g., security, integration) to a practical use case.
• Reflect on SAC’s value for industry applications.

Scope: This week covers SAC use cases across industries, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, Week 7’s SAP Cloud Platform integration, Week 8’s story creation, and Week 9’s security and data privacy. It concludes Course 1 by demonstrating SAC’s practical applications.

Background Information: SAC’s unified platform supports diverse industry needs:

• Retail: Use Case: Sales performance tracking and demand forecasting. Features: Dashboards for sales by region/product, predictive analytics for inventory planning. Example: Visualize sales trends, forecast demand using Smart Predict.
• Finance: Use Case: Budget planning and financial reporting. Features: Collaborative planning models, real-time reporting from S/4HANA. Example: Create budgets, track actuals vs. forecasts.
• Manufacturing: Use Case: Supply chain optimization and production analytics. Features: Real-time KPIs, predictive maintenance insights. Example: Monitor production efficiency, predict equipment failures.
• Healthcare: Use Case: Patient care analytics and resource planning. Features: Dashboards for patient outcomes, planning for staff allocation. Example: Analyze bed occupancy, plan staffing needs.
• Public Sector: Use Case: Budget allocation and program performance. Features: Secure reporting, planning for public funds. Example: Track program spending, ensure compliance.
• Key Benefits: Unified BI, planning, and predictive analytics reduce tool fragmentation. Native SAP integration (e.g., S/4HANA, BW/4HANA) for seamless data flows. Secure, compliant environment (GDPR, CCPA) for sensitive data.
• Challenges: Tailoring SAC to non-SAP data environments. Managing costs for large-scale industry deployments. Trial limitations may restrict advanced features (e.g., live connections).

Hands-On Example:

Scenario: You’re a business analyst for a retail company using SAC to track and analyze sales performance. Using the SAC trial, you’ll create a retail sales story with visualizations, filters, and predictive insights, simulating a real-world retail use case while applying security and integration concepts from prior weeks.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface, story creation, security, and integration (from Weeks 1–9).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model (simulating retail data).
• Modern browser (e.g., Chrome, Edge) and internet connection.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Create a Retail Sales Story:

From “Create” > “Story” > Select “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Confirm dimensions (e.g., Region, Product, Time, Store) and measures (e.g., Sales Revenue, Quantity Sold).

Set up the story:

Add a title: Click “Text” in the toolbar, enter “Retail Sales Dashboard.”

Set font size to 20pt, align center.

Add Visualizations (Retail Focus):

Bar Chart (Sales by Region):

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “Sales by Region.”

Customize: Enable data labels, set color to blue.

Geo Map (Sales by Store Location):

Click “Chart” > “Geo Map” (if available; else use a pie chart).

Drag “Sales Revenue” to Size, “Store” or “Region” to Location.

Title: “Sales by Store.”

Customize: Adjust map zoom, use gradient colors.

Table (Product Performance):

Click “Table” in the toolbar.

Add columns: “Product,” “Sales Revenue,” “Quantity Sold.”

Sort “Sales Revenue” in descending order.

Title: “Product Performance.”

KPI Tile (Total Sales):

Click “Text” or “KPI” > Add a KPI for total “Sales Revenue.”

Title: “Total Retail Sales.”

Customize: Set font size to 16pt, bold.

Arrange visuals:

Drag and resize for a clean layout (e.g., bar chart top-left, geo map top-right, table bottom-left, KPI bottom-right).

Add Filters and Input Controls:

Add a page filter:

Click “Filter” > Select “Time.”

Choose the most recent year (e.g., 2024).

Add an input control:

Click “Input Control” > Select “Product.”

Test by selecting a product; confirm visuals update.

Incorporate Predictive Analytics (Demand Forecasting):

Open the story.

Use Smart Insights:

Select the bar chart (“Sales by Region”).

Click “Smart Insights” (lightbulb icon, if available).

Create a predictive forecast:

From “Create” > “Predictive Scenario” > “Time Series Forecasting.”

Select “BestRunJuice_SampleModel” > “Sales Revenue” as the target.

Set “Time” (e.g., Month) as the date dimension.

Apply Security and Integration Concepts:

Secure the story in a folder.

Simulate SAP integration.

Validate and Troubleshoot:

Validation:

Confirm story functionality.

Troubleshooting:

Address common issues.

Interpretation: This hands-on example builds proficiency in creating a comprehensive story in SAC, combining visualizations, calculations, and interactivity in the trial environment. By designing a sales dashboard, you master SAC’s storytelling capabilities, preparing for Week 9’s focus on security and data privacy.

Supplemental Information: SAC Story Building Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud. SAC Tutorials: https://www.sap.com/products/technology-platform/analytics-cloud/resources.html.

Discussion Points:

• How does SAC’s story builder support effective data storytelling?
• What are the benefits of calculated measures for custom analytics?
• How do filters and input controls enhance stakeholder engagement?
• What challenges might arise when building complex stories in SAC?
• How does SAC’s storytelling compare to dashboards in Power BI or Tableau?

Week 9: Security and Data Privacy Overview

Introduction: Security and data privacy are critical for ensuring safe and compliant use of SAP Analytics Cloud (SAC). This week focuses on understanding SAC’s security framework, including user roles, permissions, data access controls, and compliance with privacy regulations. The emphasis is on practical usage, guiding you through exploring security settings and role-based access in the SAC trial environment to understand how SAC protects data and users.

Learning Objectives: By the end of this week, you will be able to:

• Describe SAC’s security and data privacy features.
• Understand user roles, permissions, and data access controls.
• Explore security settings and role assignments in the SAC trial.
• Identify how SAC ensures compliance with privacy regulations (e.g., GDPR, CCPA).
• Troubleshoot security-related issues in the trial environment.

Scope: This week covers SAC’s security and data privacy framework, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, Week 7’s SAP Cloud Platform integration, and Week 8’s story creation. It prepares for Week 10’s exploration of use cases across industries by ensuring an understanding of SAC’s secure environment.

Background Information: SAC’s security and data privacy features safeguard sensitive data and ensure compliance:

• Security Features: User Authentication: Single Sign-On (SSO) via SAML 2.0 or SAP Identity Authentication Service. Role-Based Access Control (RBAC): Granular permissions for users (e.g., Viewer, BI Content Creator, Planning Modeler). Data Access Controls: Restrict access to models, stories, or dimensions (e.g., region-specific data). Encryption: Data encrypted in transit (TLS) and at rest (AES-256). Audit Logging: Tracks user actions for compliance and monitoring.
• Data Privacy Compliance: Supports regulations like GDPR (EU), CCPA (California), and others. Features: Data anonymization, consent management, and data residency options. SAP’s data centers (e.g., US, EU) comply with regional privacy laws.
• Key Components: Users: Individual accounts with assigned roles. Roles: Define permissions (e.g., view, edit, share). Teams: Group users for easier permission management. Folders: Control access to content (e.g., Public, private folders).
• Applications: Restrict sales data access to regional managers. Ensure GDPR-compliant handling of customer data. Audit user activity for regulatory reporting.
• Challenges: Trial environment may limit access to advanced security settings (e.g., SSO, team management). Configuring granular data access for large organizations. Balancing security with user accessibility.

Hands-On Example:

Scenario: You’re a business analyst tasked with evaluating SAC’s security features for your organization. Using the SAC trial, you’ll explore user roles, permissions, and data access controls by creating a story, assigning access, and reviewing security settings to understand SAC’s secure environment.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface and story creation (from Weeks 1–8).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model.
• Modern browser (e.g., Chrome, Edge) and internet connection.
• Note: Trial may restrict advanced security features (e.g., multi-user management, SSO); focus on available settings.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Create a Story to Test Security:

From “Create” > “Story” > Select “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Add a visualization:

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “Secure Sales by Region.”

Enable data labels, set color to green.

Add a filter:

Click “Filter” > Select “Region” > Choose “North.”

Save the story:

Click “Save” > Name it “Secure_Sales_Story” > Save in “Public” folder.

Explore Security Settings:

Check user role:

Click the user profile (top-right) > “System” > “About.”

Note your user ID and role (trial typically assigns an admin-like role with BI and planning access).

Navigate to “Security” (if accessible):

Go to “Browse” > “Security” > “Roles.”

Observe predefined roles (e.g., BI Content Creator, Planning Modeler) and permissions.

Test Folder Permissions:

Create a private folder:

Navigate to “Files” > “Public.”

Click “New Folder” > Name it “Secure_Week9.”

Move “Secure_Sales_Story” to “Secure_Week9.”

Set folder permissions (if available).

Explore Data Access Controls:

Open “Secure_Sales_Story.”

Add a data access restriction (if available).

Simulate data access with a second story.

Review Audit and Compliance Features:

Check audit logs (if accessible).

Explore compliance settings.

Validate and Troubleshoot:

Validation:

Confirm story creation.

Troubleshooting:

Address common issues.

Interpretation: This hands-on example builds proficiency in SAC’s security and data privacy features by exploring roles, permissions, and data access controls in the trial environment. By creating stories and managing access, you gain practical insight into SAC’s secure framework, preparing for Week 10’s exploration of industry use cases.

Supplemental Information: SAC Security Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP BTP Security: https://www.sap.com/products/business-technology-platform/security.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud.

Discussion Points:

• How does SAC’s role-based access control support organizational security?
• What are the benefits of data access controls for sensitive data?
• How does SAC’s encryption ensure data privacy compliance?
• What challenges might arise when configuring security in a trial vs. production?
• How do SAC’s security features compare to Power BI or Tableau?

Week 10: Use Cases Across Industries

Introduction: SAP Analytics Cloud (SAC) is a versatile platform that supports a wide range of industry-specific use cases, from retail to finance to manufacturing. This final week explores how SAC’s business intelligence (BI), planning, and predictive analytics capabilities address real-world challenges across industries. The emphasis is on practical usage, guiding you through creating an industry-specific story in the SAC trial environment to simulate a retail sales use case, consolidating skills learned throughout the course.

Learning Objectives: By the end of this week, you will be able to:

• Identify key SAC use cases across industries (e.g., retail, finance, manufacturing).
• Understand how SAC’s features (BI, planning, predictive) solve industry challenges.
• Create an industry-specific story in SAC with visualizations and interactivity.
• Apply course concepts (e.g., security, integration) to a practical use case.
• Reflect on SAC’s value for industry applications.

Scope: This week covers SAC use cases across industries, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, Week 7’s SAP Cloud Platform integration, Week 8’s story creation, and Week 9’s security and data privacy. It concludes Course 1 by demonstrating SAC’s practical applications.

Background Information: SAC’s unified platform supports diverse industry needs:

• Retail: Use Case: Sales performance tracking and demand forecasting. Features: Dashboards for sales by region/product, predictive analytics for inventory planning. Example: Visualize sales trends, forecast demand using Smart Predict.
• Finance: Use Case: Budget planning and financial reporting. Features: Collaborative planning models, real-time reporting from S/4HANA. Example: Create budgets, track actuals vs. forecasts.
• Manufacturing: Use Case: Supply chain optimization and production analytics. Features: Real-time KPIs, predictive maintenance insights. Example: Monitor production efficiency, predict equipment failures.
• Healthcare: Use Case: Patient care analytics and resource planning. Features: Dashboards for patient outcomes, planning for staff allocation. Example: Analyze bed occupancy, plan staffing needs.
• Public Sector: Use Case: Budget allocation and program performance. Features: Secure reporting, planning for public funds. Example: Track program spending, ensure compliance.
• Key Benefits: Unified BI, planning, and predictive analytics reduce tool fragmentation. Native SAP integration (e.g., S/4HANA, BW/4HANA) for seamless data flows. Secure, compliant environment (GDPR, CCPA) for sensitive data.
• Challenges: Tailoring SAC to non-SAP data environments. Managing costs for large-scale industry deployments. Trial limitations may restrict advanced features (e.g., live connections).

Hands-On Example:

Scenario: You’re a business analyst for a retail company using SAC to track and analyze sales performance. Using the SAC trial, you’ll create a retail sales story with visualizations, filters, and predictive insights, simulating a real-world retail use case while applying security and integration concepts from prior weeks.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface, story creation, security, and integration (from Weeks 1–9).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model (simulating retail data).
• Modern browser (e.g., Chrome, Edge) and internet connection.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Create a Retail Sales Story:

From “Create” > “Story” > Select “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Confirm dimensions (e.g., Region, Product, Time, Store) and measures (e.g., Sales Revenue, Quantity Sold).

Set up the story:

Add a title: Click “Text” in the toolbar, enter “Retail Sales Dashboard.”

Set font size to 20pt, align center.

Add Visualizations (Retail Focus):

Bar Chart (Sales by Region):

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “Sales by Region.”

Customize: Enable data labels, set color to blue.

Geo Map (Sales by Store Location):

Click “Chart” > “Geo Map” (if available; else use a pie chart).

Drag “Sales Revenue” to Size, “Store” or “Region” to Location.

Title: “Sales by Store.”

Customize: Adjust map zoom, use gradient colors.

Table (Product Performance):

Click “Table” in the toolbar.

Add columns: “Product,” “Sales Revenue,” “Quantity Sold.”

Sort “Sales Revenue” in descending order.

Title: “Product Performance.”

KPI Tile (Total Sales):

Click “Text” or “KPI” > Add a KPI for total “Sales Revenue.”

Title: “Total Retail Sales.”

Customize: Set font size to 16pt, bold.

Arrange visuals:

Drag and resize for a clean layout (e.g., bar chart top-left, geo map top-right, table bottom-left, KPI bottom-right).

Add Filters and Input Controls:

Add a page filter:

Click “Filter” > Select “Time.”

Choose the most recent year (e.g., 2024).

Add an input control:

Click “Input Control” > Select “Product.”

Test by selecting a product; confirm visuals update.

Incorporate Predictive Analytics (Demand Forecasting):

Open the story.

Use Smart Insights:

Select the bar chart (“Sales by Region”).

Click “Smart Insights” (lightbulb icon, if available).

Create a predictive forecast:

From “Create” > “Predictive Scenario” > “Time Series Forecasting.”

Select “BestRunJuice_SampleModel” > “Sales Revenue” as the target.

Set “Time” (e.g., Month) as the date dimension.

Apply Security and Integration Concepts:

Secure the story in a folder.

Simulate SAP integration.

Validate and Troubleshoot:

Validation:

Confirm story functionality.

Troubleshooting:

Address common issues.

Interpretation: This hands-on example builds proficiency in creating a comprehensive story in SAC, combining visualizations, calculations, and interactivity in the trial environment. By designing a sales dashboard, you master SAC’s storytelling capabilities, preparing for Week 9’s focus on security and data privacy.

Supplemental Information: SAC Story Building Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud. SAC Tutorials: https://www.sap.com/products/technology-platform/analytics-cloud/resources.html.

Discussion Points:

• How does SAC’s story builder support effective data storytelling?
• What are the benefits of calculated measures for custom analytics?
• How do filters and input controls enhance stakeholder engagement?
• What challenges might arise when building complex stories in SAC?
• How does SAC’s storytelling compare to dashboards in Power BI or Tableau?

Week 9: Security and Data Privacy Overview

Introduction: Security and data privacy are critical for ensuring safe and compliant use of SAP Analytics Cloud (SAC). This week focuses on understanding SAC’s security framework, including user roles, permissions, data access controls, and compliance with privacy regulations. The emphasis is on practical usage, guiding you through exploring security settings and role-based access in the SAC trial environment to understand how SAC protects data and users.

Learning Objectives: By the end of this week, you will be able to:

• Describe SAC’s security and data privacy features.
• Understand user roles, permissions, and data access controls.
• Explore security settings and role assignments in the SAC trial.
• Identify how SAC ensures compliance with privacy regulations (e.g., GDPR, CCPA).
• Troubleshoot security-related issues in the trial environment.

Scope: This week covers SAC’s security and data privacy framework, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, Week 7’s SAP Cloud Platform integration, and Week 8’s story creation. It prepares for Week 10’s exploration of use cases across industries by ensuring an understanding of SAC’s secure environment.

Background Information: SAC’s security and data privacy features safeguard sensitive data and ensure compliance:

• Security Features: User Authentication: Single Sign-On (SSO) via SAML 2.0 or SAP Identity Authentication Service. Role-Based Access Control (RBAC): Granular permissions for users (e.g., Viewer, BI Content Creator, Planning Modeler). Data Access Controls: Restrict access to models, stories, or dimensions (e.g., region-specific data). Encryption: Data encrypted in transit (TLS) and at rest (AES-256). Audit Logging: Tracks user actions for compliance and monitoring.
• Data Privacy Compliance: Supports regulations like GDPR (EU), CCPA (California), and others. Features: Data anonymization, consent management, and data residency options. SAP’s data centers (e.g., US, EU) comply with regional privacy laws.
• Key Components: Users: Individual accounts with assigned roles. Roles: Define permissions (e.g., view, edit, share). Teams: Group users for easier permission management. Folders: Control access to content (e.g., Public, private folders).
• Applications: Restrict sales data access to regional managers. Ensure GDPR-compliant handling of customer data. Audit user activity for regulatory reporting.
• Challenges: Trial environment may limit access to advanced security settings (e.g., SSO, team management). Configuring granular data access for large organizations. Balancing security with user accessibility.

Hands-On Example:

Scenario: You’re a business analyst tasked with evaluating SAC’s security features for your organization. Using the SAC trial, you’ll explore user roles, permissions, and data access controls by creating a story, assigning access, and reviewing security settings to understand SAC’s secure environment.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface and story creation (from Weeks 1–8).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model.
• Modern browser (e.g., Chrome, Edge) and internet connection.
• Note: Trial may restrict advanced security features (e.g., multi-user management, SSO); focus on available settings.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Create a Story to Test Security:

From “Create” > “Story” > Select “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Add a visualization:

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “Secure Sales by Region.”

Enable data labels, set color to green.

Add a filter:

Click “Filter” > Select “Region” > Choose “North.”

Save the story:

Click “Save” > Name it “Secure_Sales_Story” > Save in “Public” folder.

Explore Security Settings:

Check user role:

Click the user profile (top-right) > “System” > “About.”

Note your user ID and role (trial typically assigns an admin-like role with BI and planning access).

Navigate to “Security” (if accessible):

Go to “Browse” > “Security” > “Roles.”

Observe predefined roles (e.g., BI Content Creator, Planning Modeler) and permissions.

Test Folder Permissions:

Create a private folder:

Navigate to “Files” > “Public.”

Click “New Folder” > Name it “Secure_Week9.”

Move “Secure_Sales_Story” to “Secure_Week9.”

Set folder permissions (if available).

Explore Data Access Controls:

Open “Secure_Sales_Story.”

Add a data access restriction (if available).

Simulate data access with a second story.

Review Audit and Compliance Features:

Check audit logs (if accessible).

Explore compliance settings.

Validate and Troubleshoot:

Validation:

Confirm story creation.

Troubleshooting:

Address common issues.

Interpretation: This hands-on example builds proficiency in SAC’s security and data privacy features by exploring roles, permissions, and data access controls in the trial environment. By creating stories and managing access, you gain practical insight into SAC’s secure framework, preparing for Week 10’s exploration of industry use cases.

Supplemental Information: SAC Security Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP BTP Security: https://www.sap.com/products/business-technology-platform/security.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud.

Discussion Points:

• How does SAC’s role-based access control support organizational security?
• What are the benefits of data access controls for sensitive data?
• How does SAC’s encryption ensure data privacy compliance?
• What challenges might arise when configuring security in a trial vs. production?
• How do SAC’s security features compare to Power BI or Tableau?

Week 10: Use Cases Across Industries

Introduction: SAP Analytics Cloud (SAC) is a versatile platform that supports a wide range of industry-specific use cases, from retail to finance to manufacturing. This final week explores how SAC’s business intelligence (BI), planning, and predictive analytics capabilities address real-world challenges across industries. The emphasis is on practical usage, guiding you through creating an industry-specific story in the SAC trial environment to simulate a retail sales use case, consolidating skills learned throughout the course.

Learning Objectives: By the end of this week, you will be able to:

• Identify key SAC use cases across industries (e.g., retail, finance, manufacturing).
• Understand how SAC’s features (BI, planning, predictive) solve industry challenges.
• Create an industry-specific story in SAC with visualizations and interactivity.
• Apply course concepts (e.g., security, integration) to a practical use case.
• Reflect on SAC’s value for industry applications.

Scope: This week covers SAC use cases across industries, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, Week 7’s SAP Cloud Platform integration, Week 8’s story creation, and Week 9’s security and data privacy. It concludes Course 1 by demonstrating SAC’s practical applications.

Background Information: SAC’s unified platform supports diverse industry needs:

• Retail: Use Case: Sales performance tracking and demand forecasting. Features: Dashboards for sales by region/product, predictive analytics for inventory planning. Example: Visualize sales trends, forecast demand using Smart Predict.
• Finance: Use Case: Budget planning and financial reporting. Features: Collaborative planning models, real-time reporting from S/4HANA. Example: Create budgets, track actuals vs. forecasts.
• Manufacturing: Use Case: Supply chain optimization and production analytics. Features: Real-time KPIs, predictive maintenance insights. Example: Monitor production efficiency, predict equipment failures.
• Healthcare: Use Case: Patient care analytics and resource planning. Features: Dashboards for patient outcomes, planning for staff allocation. Example: Analyze bed occupancy, plan staffing needs.
• Public Sector: Use Case: Budget allocation and program performance. Features: Secure reporting, planning for public funds. Example: Track program spending, ensure compliance.
• Key Benefits: Unified BI, planning, and predictive analytics reduce tool fragmentation. Native SAP integration (e.g., S/4HANA, BW/4HANA) for seamless data flows. Secure, compliant environment (GDPR, CCPA) for sensitive data.
• Challenges: Tailoring SAC to non-SAP data environments. Managing costs for large-scale industry deployments. Trial limitations may restrict advanced features (e.g., live connections).

Hands-On Example:

Scenario: You’re a business analyst for a retail company using SAC to track and analyze sales performance. Using the SAC trial, you’ll create a retail sales story with visualizations, filters, and predictive insights, simulating a real-world retail use case while applying security and integration concepts from prior weeks.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface, story creation, security, and integration (from Weeks 1–9).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model (simulating retail data).
• Modern browser (e.g., Chrome, Edge) and internet connection.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Create a Retail Sales Story:

From “Create” > “Story” > Select “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Confirm dimensions (e.g., Region, Product, Time, Store) and measures (e.g., Sales Revenue, Quantity Sold).

Set up the story:

Add a title: Click “Text” in the toolbar, enter “Retail Sales Dashboard.”

Set font size to 20pt, align center.

Add Visualizations (Retail Focus):

Bar Chart (Sales by Region):

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “Sales by Region.”

Customize: Enable data labels, set color to blue.

Geo Map (Sales by Store Location):

Click “Chart” > “Geo Map” (if available; else use a pie chart).

Drag “Sales Revenue” to Size, “Store” or “Region” to Location.

Title: “Sales by Store.”

Customize: Adjust map zoom, use gradient colors.

Table (Product Performance):

Click “Table” in the toolbar.

Add columns: “Product,” “Sales Revenue,” “Quantity Sold.”

Sort “Sales Revenue” in descending order.

Title: “Product Performance.”

KPI Tile (Total Sales):

Click “Text” or “KPI” > Add a KPI for total “Sales Revenue.”

Title: “Total Retail Sales.”

Customize: Set font size to 16pt, bold.

Arrange visuals:

Drag and resize for a clean layout (e.g., bar chart top-left, geo map top-right, table bottom-left, KPI bottom-right).

Add Filters and Input Controls:

Add a page filter:

Click “Filter” > Select “Time.”

Choose the most recent year (e.g., 2024).

Add an input control:

Click “Input Control” > Select “Product.”

Test by selecting a product; confirm visuals update.

Incorporate Predictive Analytics (Demand Forecasting):

Open the story.

Use Smart Insights:

Select the bar chart (“Sales by Region”).

Click “Smart Insights” (lightbulb icon, if available).

Create a predictive forecast:

From “Create” > “Predictive Scenario” > “Time Series Forecasting.”

Select “BestRunJuice_SampleModel” > “Sales Revenue” as the target.

Set “Time” (e.g., Month) as the date dimension.

Apply Security and Integration Concepts:

Secure the story in a folder.

Simulate SAP integration.

Validate and Troubleshoot:

Validation:

Confirm story functionality.

Troubleshooting:

Address common issues.

Interpretation: This hands-on example builds proficiency in creating a comprehensive story in SAC, combining visualizations, calculations, and interactivity in the trial environment. By designing a sales dashboard, you master SAC’s storytelling capabilities, preparing for Week 9’s focus on security and data privacy.

Supplemental Information: SAC Story Building Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud. SAC Tutorials: https://www.sap.com/products/technology-platform/analytics-cloud/resources.html.

Discussion Points:

• How does SAC’s story builder support effective data storytelling?
• What are the benefits of calculated measures for custom analytics?
• How do filters and input controls enhance stakeholder engagement?
• What challenges might arise when building complex stories in SAC?
• How does SAC’s storytelling compare to dashboards in Power BI or Tableau?

Week 9: Security and Data Privacy Overview

Introduction: Security and data privacy are critical for ensuring safe and compliant use of SAP Analytics Cloud (SAC). This week focuses on understanding SAC’s security framework, including user roles, permissions, data access controls, and compliance with privacy regulations. The emphasis is on practical usage, guiding you through exploring security settings and role-based access in the SAC trial environment to understand how SAC protects data and users.

Learning Objectives: By the end of this week, you will be able to:

• Describe SAC’s security and data privacy features.
• Understand user roles, permissions, and data access controls.
• Explore security settings and role assignments in the SAC trial.
• Identify how SAC ensures compliance with privacy regulations (e.g., GDPR, CCPA).
• Troubleshoot security-related issues in the trial environment.

Scope: This week covers SAC’s security and data privacy framework, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, Week 7’s SAP Cloud Platform integration, and Week 8’s story creation. It prepares for Week 10’s exploration of use cases across industries by ensuring an understanding of SAC’s secure environment.

Background Information: SAC’s security and data privacy features safeguard sensitive data and ensure compliance:

• Security Features: User Authentication: Single Sign-On (SSO) via SAML 2.0 or SAP Identity Authentication Service. Role-Based Access Control (RBAC): Granular permissions for users (e.g., Viewer, BI Content Creator, Planning Modeler). Data Access Controls: Restrict access to models, stories, or dimensions (e.g., region-specific data). Encryption: Data encrypted in transit (TLS) and at rest (AES-256). Audit Logging: Tracks user actions for compliance and monitoring.
• Data Privacy Compliance: Supports regulations like GDPR (EU), CCPA (California), and others. Features: Data anonymization, consent management, and data residency options. SAP’s data centers (e.g., US, EU) comply with regional privacy laws.
• Key Components: Users: Individual accounts with assigned roles. Roles: Define permissions (e.g., view, edit, share). Teams: Group users for easier permission management. Folders: Control access to content (e.g., Public, private folders).
• Applications: Restrict sales data access to regional managers. Ensure GDPR-compliant handling of customer data. Audit user activity for regulatory reporting.
• Challenges: Trial environment may limit access to advanced security settings (e.g., SSO, team management). Configuring granular data access for large organizations. Balancing security with user accessibility.

Hands-On Example:

Scenario: You’re a business analyst tasked with evaluating SAC’s security features for your organization. Using the SAC trial, you’ll explore user roles, permissions, and data access controls by creating a story, assigning access, and reviewing security settings to understand SAC’s secure environment.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface and story creation (from Weeks 1–8).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model.
• Modern browser (e.g., Chrome, Edge) and internet connection.
• Note: Trial may restrict advanced security features (e.g., multi-user management, SSO); focus on available settings.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Create a Story to Test Security:

From “Create” > “Story” > Select “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Add a visualization:

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “Secure Sales by Region.”

Enable data labels, set color to green.

Add a filter:

Click “Filter” > Select “Region” > Choose “North.”

Save the story:

Click “Save” > Name it “Secure_Sales_Story” > Save in “Public” folder.

Explore Security Settings:

Check user role:

Click the user profile (top-right) > “System” > “About.”

Note your user ID and role (trial typically assigns an admin-like role with BI and planning access).

Navigate to “Security” (if accessible):

Go to “Browse” > “Security” > “Roles.”

Observe predefined roles (e.g., BI Content Creator, Planning Modeler) and permissions.

Test Folder Permissions:

Create a private folder:

Navigate to “Files” > “Public.”

Click “New Folder” > Name it “Secure_Week9.”

Move “Secure_Sales_Story” to “Secure_Week9.”

Set folder permissions (if available).

Explore Data Access Controls:

Open “Secure_Sales_Story.”

Add a data access restriction (if available).

Simulate data access with a second story.

Review Audit and Compliance Features:

Check audit logs (if accessible).

Explore compliance settings.

Validate and Troubleshoot:

Validation:

Confirm story creation.

Troubleshooting:

Address common issues.

Interpretation: This hands-on example builds proficiency in SAC’s security and data privacy features by exploring roles, permissions, and data access controls in the trial environment. By creating stories and managing access, you gain practical insight into SAC’s secure framework, preparing for Week 10’s exploration of industry use cases.

Supplemental Information: SAC Security Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP BTP Security: https://www.sap.com/products/business-technology-platform/security.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud.

Discussion Points:

• How does SAC’s role-based access control support organizational security?
• What are the benefits of data access controls for sensitive data?
• How does SAC’s encryption ensure data privacy compliance?
• What challenges might arise when configuring security in a trial vs. production?
• How do SAC’s security features compare to Power BI or Tableau?

Week 10: Use Cases Across Industries

Introduction: SAP Analytics Cloud (SAC) is a versatile platform that supports a wide range of industry-specific use cases, from retail to finance to manufacturing. This final week explores how SAC’s business intelligence (BI), planning, and predictive analytics capabilities address real-world challenges across industries. The emphasis is on practical usage, guiding you through creating an industry-specific story in the SAC trial environment to simulate a retail sales use case, consolidating skills learned throughout the course.

Learning Objectives: By the end of this week, you will be able to:

• Identify key SAC use cases across industries (e.g., retail, finance, manufacturing).
• Understand how SAC’s features (BI, planning, predictive) solve industry challenges.
• Create an industry-specific story in SAC with visualizations and interactivity.
• Apply course concepts (e.g., security, integration) to a practical use case.
• Reflect on SAC’s value for industry applications.

Scope: This week covers SAC use cases across industries, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, Week 7’s SAP Cloud Platform integration, Week 8’s story creation, and Week 9’s security and data privacy. It concludes Course 1 by demonstrating SAC’s practical applications.

Background Information: SAC’s unified platform supports diverse industry needs:

• Retail: Use Case: Sales performance tracking and demand forecasting. Features: Dashboards for sales by region/product, predictive analytics for inventory planning. Example: Visualize sales trends, forecast demand using Smart Predict.
• Finance: Use Case: Budget planning and financial reporting. Features: Collaborative planning models, real-time reporting from S/4HANA. Example: Create budgets, track actuals vs. forecasts.
• Manufacturing: Use Case: Supply chain optimization and production analytics. Features: Real-time KPIs, predictive maintenance insights. Example: Monitor production efficiency, predict equipment failures.
• Healthcare: Use Case: Patient care analytics and resource planning. Features: Dashboards for patient outcomes, planning for staff allocation. Example: Analyze bed occupancy, plan staffing needs.
• Public Sector: Use Case: Budget allocation and program performance. Features: Secure reporting, planning for public funds. Example: Track program spending, ensure compliance.
• Key Benefits: Unified BI, planning, and predictive analytics reduce tool fragmentation. Native SAP integration (e.g., S/4HANA, BW/4HANA) for seamless data flows. Secure, compliant environment (GDPR, CCPA) for sensitive data.
• Challenges: Tailoring SAC to non-SAP data environments. Managing costs for large-scale industry deployments. Trial limitations may restrict advanced features (e.g., live connections).

Hands-On Example:

Scenario: You’re a business analyst for a retail company using SAC to track and analyze sales performance. Using the SAC trial, you’ll create a retail sales story with visualizations, filters, and predictive insights, simulating a real-world retail use case while applying security and integration concepts from prior weeks.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface, story creation, security, and integration (from Weeks 1–9).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model (simulating retail data).
• Modern browser (e.g., Chrome, Edge) and internet connection.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Create a Retail Sales Story:

From “Create” > “Story” > Select “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Confirm dimensions (e.g., Region, Product, Time, Store) and measures (e.g., Sales Revenue, Quantity Sold).

Set up the story:

Add a title: Click “Text” in the toolbar, enter “Retail Sales Dashboard.”

Set font size to 20pt, align center.

Add Visualizations (Retail Focus):

Bar Chart (Sales by Region):

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “Sales by Region.”

Customize: Enable data labels, set color to blue.

Geo Map (Sales by Store Location):

Click “Chart” > “Geo Map” (if available; else use a pie chart).

Drag “Sales Revenue” to Size, “Store” or “Region” to Location.

Title: “Sales by Store.”

Customize: Adjust map zoom, use gradient colors.

Table (Product Performance):

Click “Table” in the toolbar.

Add columns: “Product,” “Sales Revenue,” “Quantity Sold.”

Sort “Sales Revenue” in descending order.

Title: “Product Performance.”

KPI Tile (Total Sales):

Click “Text” or “KPI” > Add a KPI for total “Sales Revenue.”

Title: “Total Retail Sales.”

Customize: Set font size to 16pt, bold.

Arrange visuals:

Drag and resize for a clean layout (e.g., bar chart top-left, geo map top-right, table bottom-left, KPI bottom-right).

Add Filters and Input Controls:

Add a page filter:

Click “Filter” > Select “Time.”

Choose the most recent year (e.g., 2024).

Add an input control:

Click “Input Control” > Select “Product.”

Test by selecting a product; confirm visuals update.

Incorporate Predictive Analytics (Demand Forecasting):

Open the story.

Use Smart Insights:

Select the bar chart (“Sales by Region”).

Click “Smart Insights” (lightbulb icon, if available).

Create a predictive forecast:

From “Create” > “Predictive Scenario” > “Time Series Forecasting.”

Select “BestRunJuice_SampleModel” > “Sales Revenue” as the target.

Set “Time” (e.g., Month) as the date dimension.

Apply Security and Integration Concepts:

Secure the story in a folder.

Simulate SAP integration.

Validate and Troubleshoot:

Validation:

Confirm story functionality.

Troubleshooting:

Address common issues.

Interpretation: This hands-on example builds proficiency in creating a comprehensive story in SAC, combining visualizations, calculations, and interactivity in the trial environment. By designing a sales dashboard, you master SAC’s storytelling capabilities, preparing for Week 9’s focus on security and data privacy.

Supplemental Information: SAC Story Building Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud. SAC Tutorials: https://www.sap.com/products/technology-platform/analytics-cloud/resources.html.

Discussion Points:

• How does SAC’s story builder support effective data storytelling?
• What are the benefits of calculated measures for custom analytics?
• How do filters and input controls enhance stakeholder engagement?
• What challenges might arise when building complex stories in SAC?
• How does SAC’s storytelling compare to dashboards in Power BI or Tableau?

Week 9: Security and Data Privacy Overview

Introduction: Security and data privacy are critical for ensuring safe and compliant use of SAP Analytics Cloud (SAC). This week focuses on understanding SAC’s security framework, including user roles, permissions, data access controls, and compliance with privacy regulations. The emphasis is on practical usage, guiding you through exploring security settings and role-based access in the SAC trial environment to understand how SAC protects data and users.

Learning Objectives: By the end of this week, you will be able to:

• Describe SAC’s security and data privacy features.
• Understand user roles, permissions, and data access controls.
• Explore security settings and role assignments in the SAC trial.
• Identify how SAC ensures compliance with privacy regulations (e.g., GDPR, CCPA).
• Troubleshoot security-related issues in the trial environment.

Scope: This week covers SAC’s security and data privacy framework, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, Week 7’s SAP Cloud Platform integration, and Week 8’s story creation. It prepares for Week 10’s exploration of use cases across industries by ensuring an understanding of SAC’s secure environment.

Background Information: SAC’s security and data privacy features safeguard sensitive data and ensure compliance:

• Security Features: User Authentication: Single Sign-On (SSO) via SAML 2.0 or SAP Identity Authentication Service. Role-Based Access Control (RBAC): Granular permissions for users (e.g., Viewer, BI Content Creator, Planning Modeler). Data Access Controls: Restrict access to models, stories, or dimensions (e.g., region-specific data). Encryption: Data encrypted in transit (TLS) and at rest (AES-256). Audit Logging: Tracks user actions for compliance and monitoring.
• Data Privacy Compliance: Supports regulations like GDPR (EU), CCPA (California), and others. Features: Data anonymization, consent management, and data residency options. SAP’s data centers (e.g., US, EU) comply with regional privacy laws.
• Key Components: Users: Individual accounts with assigned roles. Roles: Define permissions (e.g., view, edit, share). Teams: Group users for easier permission management. Folders: Control access to content (e.g., Public, private folders).
• Applications: Restrict sales data access to regional managers. Ensure GDPR-compliant handling of customer data. Audit user activity for regulatory reporting.
• Challenges: Trial environment may limit access to advanced security settings (e.g., SSO, team management). Configuring granular data access for large organizations. Balancing security with user accessibility.

Hands-On Example:

Scenario: You’re a business analyst tasked with evaluating SAC’s security features for your organization. Using the SAC trial, you’ll explore user roles, permissions, and data access controls by creating a story, assigning access, and reviewing security settings to understand SAC’s secure environment.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface and story creation (from Weeks 1–8).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model.
• Modern browser (e.g., Chrome, Edge) and internet connection.
• Note: Trial may restrict advanced security features (e.g., multi-user management, SSO); focus on available settings.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Create a Story to Test Security:

From “Create” > “Story” > Select “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Add a visualization:

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “Secure Sales by Region.”

Enable data labels, set color to green.

Add a filter:

Click “Filter” > Select “Region” > Choose “North.”

Save the story:

Click “Save” > Name it “Secure_Sales_Story” > Save in “Public” folder.

Explore Security Settings:

Check user role:

Click the user profile (top-right) > “System” > “About.”

Note your user ID and role (trial typically assigns an admin-like role with BI and planning access).

Navigate to “Security” (if accessible):

Go to “Browse” > “Security” > “Roles.”

Observe predefined roles (e.g., BI Content Creator, Planning Modeler) and permissions.

Test Folder Permissions:

Create a private folder:

Navigate to “Files” > “Public.”

Click “New Folder” > Name it “Secure_Week9.”

Move “Secure_Sales_Story” to “Secure_Week9.”

Set folder permissions (if available).

Explore Data Access Controls:

Open “Secure_Sales_Story.”

Add a data access restriction (if available).

Simulate data access with a second story.

Review Audit and Compliance Features:

Check audit logs (if accessible).

Explore compliance settings.

Validate and Troubleshoot:

Validation:

Confirm story creation.

Troubleshooting:

Address common issues.

Interpretation: This hands-on example builds proficiency in SAC’s security and data privacy features by exploring roles, permissions, and data access controls in the trial environment. By creating stories and managing access, you gain practical insight into SAC’s secure framework, preparing for Week 10’s exploration of industry use cases.

Supplemental Information: SAC Security Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP BTP Security: https://www.sap.com/products/business-technology-platform/security.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud.

Discussion Points:

• How does SAC’s role-based access control support organizational security?
• What are the benefits of data access controls for sensitive data?
• How does SAC’s encryption ensure data privacy compliance?
• What challenges might arise when configuring security in a trial vs. production?
• How do SAC’s security features compare to Power BI or Tableau?

Week 10: Use Cases Across Industries

Introduction: SAP Analytics Cloud (SAC) is a versatile platform that supports a wide range of industry-specific use cases, from retail to finance to manufacturing. This final week explores how SAC’s business intelligence (BI), planning, and predictive analytics capabilities address real-world challenges across industries. The emphasis is on practical usage, guiding you through creating an industry-specific story in the SAC trial environment to simulate a retail sales use case, consolidating skills learned throughout the course.

Learning Objectives: By the end of this week, you will be able to:

• Identify key SAC use cases across industries (e.g., retail, finance, manufacturing).
• Understand how SAC’s features (BI, planning, predictive) solve industry challenges.
• Create an industry-specific story in SAC with visualizations and interactivity.
• Apply course concepts (e.g., security, integration) to a practical use case.
• Reflect on SAC’s value for industry applications.

Scope: This week covers SAC use cases across industries, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, Week 7’s SAP Cloud Platform integration, Week 8’s story creation, and Week 9’s security and data privacy. It concludes Course 1 by demonstrating SAC’s practical applications.

Background Information: SAC’s unified platform supports diverse industry needs:

• Retail: Use Case: Sales performance tracking and demand forecasting. Features: Dashboards for sales by region/product, predictive analytics for inventory planning. Example: Visualize sales trends, forecast demand using Smart Predict.
• Finance: Use Case: Budget planning and financial reporting. Features: Collaborative planning models, real-time reporting from S/4HANA. Example: Create budgets, track actuals vs. forecasts.
• Manufacturing: Use Case: Supply chain optimization and production analytics. Features: Real-time KPIs, predictive maintenance insights. Example: Monitor production efficiency, predict equipment failures.
• Healthcare: Use Case: Patient care analytics and resource planning. Features: Dashboards for patient outcomes, planning for staff allocation. Example: Analyze bed occupancy, plan staffing needs.
• Public Sector: Use Case: Budget allocation and program performance. Features: Secure reporting, planning for public funds. Example: Track program spending, ensure compliance.
• Key Benefits: Unified BI, planning, and predictive analytics reduce tool fragmentation. Native SAP integration (e.g., S/4HANA, BW/4HANA) for seamless data flows. Secure, compliant environment (GDPR, CCPA) for sensitive data.
• Challenges: Tailoring SAC to non-SAP data environments. Managing costs for large-scale industry deployments. Trial limitations may restrict advanced features (e.g., live connections).

Hands-On Example:

Scenario: You’re a business analyst for a retail company using SAC to track and analyze sales performance. Using the SAC trial, you’ll create a retail sales story with visualizations, filters, and predictive insights, simulating a real-world retail use case while applying security and integration concepts from prior weeks.

Prerequisites:

• Active SAC trial account (set up in Week 1; access via https://.sapanalytics.cloud/).
• Familiarity with SAC’s interface, story creation, security, and integration (from Weeks 1–9).
• Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model (simulating retail data).
• Modern browser (e.g., Chrome, Edge) and internet connection.

Step-by-Step Instructions:

Access the SAC Trial Environment:

Log in to your SAC trial account (https://.sapanalytics.cloud/).

Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.”

Create a Retail Sales Story:

From “Create” > “Story” > Select “Canvas” mode.

Add a data source:

Click “Add Data” > “Data from a Model.”

Select “BestRunJuice_SampleModel” (or equivalent sales model).

Confirm dimensions (e.g., Region, Product, Time, Store) and measures (e.g., Sales Revenue, Quantity Sold).

Set up the story:

Add a title: Click “Text” in the toolbar, enter “Retail Sales Dashboard.”

Set font size to 20pt, align center.

Add Visualizations (Retail Focus):

Bar Chart (Sales by Region):

Click “Chart” > “Bar/Column.”

Drag “Sales Revenue” to Y-axis, “Region” to X-axis.

Title: “Sales by Region.”

Customize: Enable data labels, set color to blue.

Geo Map (Sales by Store Location):

Click “Chart” > “Geo Map” (if available; else use a pie chart).

Drag “Sales Revenue” to Size, “Store” or “Region” to Location.

Title: “Sales by Store.”

Customize: Adjust map zoom, use gradient colors.

Table (Product Performance):

Click “Table” in the toolbar.

Add columns: “Product,” “Sales Revenue,” “Quantity Sold.”

Sort “Sales Revenue” in descending order.

Title: “Product Performance.”

KPI Tile (Total Sales):

Click “Text” or “KPI” > Add a KPI for total “Sales Revenue.”

Title: “Total Retail Sales.”

Customize: Set font size to 16pt, bold.

Arrange visuals:

Drag and resize for a clean layout (e.g., bar chart top-left, geo map top-right, table bottom-left, KPI bottom-right).

Add Filters and Input Controls:

Add a page filter:

Click “Filter” > Select “Time.”

Choose the most recent year (e.g., 2024).

Add an input control:

Click “Input Control” > Select “Product.”

Test by selecting a product; confirm visuals update.

Incorporate Predictive Analytics (Demand Forecasting):

Open the story.

Use Smart Insights:

Select the bar chart (“Sales by Region”).

Click “Smart Insights” (lightbulb icon, if available).

Create a predictive forecast:

From “Create” > “Predictive Scenario” > “Time Series Forecasting.”

Select “BestRunJuice_SampleModel” > “Sales Revenue” as the target.

Set “Time” (e.g., Month) as the date dimension.

Apply Security and Integration Concepts:

Secure the story in a folder.

Simulate SAP integration.

Validate and Troubleshoot:

Validation:

Confirm story functionality.

Troubleshooting:

Address common issues.

Interpretation: This hands-on example builds proficiency in creating a comprehensive story in SAC, combining visualizations, calculations, and interactivity in the trial environment. By designing a sales dashboard, you master SAC’s storytelling capabilities, preparing for Week 9’s focus on security and data privacy.

Supplemental Information: SAC Story Building Guide: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bf9e33a3f7b649e097f4c9e3adbc6064.html. SAP Community for SAC: https://community.sap.com/topics/analytics-cloud. SAC Tutorials: https://www.sap.com/products/technology-platform/analytics-cloud/resources.html.

Discussion Points:

• How does SAC’s story builder support effective data storytelling?
• What are the benefits of calculated measures for custom analytics?
• How do filters and input controls enhance stakeholder engagement?
• What challenges might arise when building complex stories in SAC?
• How does SAC’s storytelling compare to dashboards in Power BI or Tableau?

Week 9: Security and Data Privacy Overview

Introduction: Security and data privacy are critical for ensuring safe and compliant use of SAP Analytics Cloud (SAC). This week focuses on understanding SAC’s security framework, including user roles, permissions, data access controls, and compliance with privacy regulations. The emphasis is on practical usage, guiding you through exploring security settings and role-based access in the SAC trial environment to understand how SAC protects data and users.

Learning Objectives: By the end of this week, you will be able to:

• Describe SAC’s security and data privacy features.
• Understand user roles, permissions, and data access controls.
• Explore security settings and role assignments in the SAC trial.
• Identify how SAC ensures compliance with privacy regulations (e.g., GDPR, CCPA).
• Troubleshoot security-related issues in the trial environment.

Scope: This week covers SAC’s security and data privacy framework, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, Week 7’s SAP Cloud Platform integration, and Week 8’s story creation. It prepares for Week 10’s exploration of use cases across industries by ensuring an understanding of SAC’s secure environment.

Background Information: SAC’s security and data privacy features safeguard sensitive data and ensure compliance:

• Security Features: User Authentication: Single Sign-On (SSO) via SAML 2.0 or SAP Identity Authentication Service. Role-Based Access Control (RBAC): Granular permissions for users (e.g., Viewer, BI Content Creator, Planning Modeler). Data Access Controls: Restrict access to models, stories, or dimensions (e.g., region-specific data). Encryption: Data encrypted in transit (TLS) and at rest (AES-256). Audit Logging: Tracks user actions for compliance and monitoring.
• Data Privacy Compliance: Supports regulations like GDPR (EU), CCPA (California), and others. Features: Data anonymization, consent management, and data residency options. SAP’s data centers (e.g., US, EU) comply with regional privacy laws.
• Key Components: Users: Individual accounts with assigned roles. Roles: Define permissions (e.g., view, edit, share). Teams: Group users for easier permission management. Folders: Control access to content (e.g., Public, private folders).
• Applications: Restrict sales data access to regional managers. Ensure GDPR-compliant handling of customer data. Audit user activity for regulatory reporting.
• Challenges: Trial environment may limit access to advanced security settings (e.g., SSO, team management). Configuring granular data access for large organizations. Balancing security with user accessibility.

Hands-On Example: Scenario: You’re a business analyst tasked with evaluating SAC’s security features for your organization. Using the SAC trial, you’ll explore user roles, permissions, and data access controls by creating a story, assigning access, and reviewing security settings to understand SAC’s secure environment.

• Prerequisites: Active SAC trial account (set up in Week 1; access via https://<tenant>.sapanalytics.cloud/). Familiarity with SAC’s interface and story creation (from Weeks 1–8). Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model. Modern browser (e.g., Chrome, Edge) and internet connection. Note: Trial may restrict advanced security features (e.g., multi-user management, SSO); focus on available settings.
• Step-by-Step Instructions: Access the SAC Trial Environment: Log in to your SAC trial account (https://<tenant>.sapanalytics.cloud/). Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.” Navigate to “Files” > “Samples” to confirm access to “BestRunJuice_SampleModel.” Create a Story to Test Security: From “Create” > “Story” > “Canvas” mode. Add a data source: Click “Add Data” > “Data from a Model.” Select “BestRunJuice_SampleModel.” Add a visualization: Click “Chart” > “Bar/Column.” Drag “Sales Revenue” to Y-axis, “Region” to X-axis. Title: “Secure Sales by Region.” Add a filter: Click “Filter” > Select “Region” > Choose “North.” Save the story: Click “Save” > Name it “Secure_Sales_Story” > Save in “Public” folder. Explore Security Settings: Check user role: Click the user profile > “System” > “About.” Navigate to “Security” > “Roles.” Observe roles and permissions. Test Folder Permissions: Create a folder: “Secure_Week9.” Move the story and set permissions. Explore Data Access Controls: Create a second story with filtered data. Review Audit and Compliance Features: Check audit logs if accessible. Verify: Stories and security settings function as expected. Output: Stories demonstrating security features. Proficiency in managing SAC’s security.
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Week 10: Use Cases Across Industries

Introduction: SAP Analytics Cloud (SAC) is a versatile platform that supports a wide range of industry-specific use cases, from retail to finance to manufacturing. This final week explores how SAC’s business intelligence (BI), planning, and predictive analytics capabilities address real-world challenges across industries. The emphasis is on practical usage, guiding you through creating an industry-specific story in the SAC trial environment to simulate a retail sales use case, consolidating skills learned throughout the course.

Learning Objectives: By the end of this week, you will be able to:

• Identify key SAC use cases across industries (e.g., retail, finance, manufacturing).
• Understand how SAC’s features (BI, planning, predictive) solve industry challenges.
• Create an industry-specific story in SAC with visualizations and interactivity.
• Apply course concepts (e.g., security, integration) to a practical use case.
• Reflect on SAC’s value for industry applications.

Scope: This week covers SAC use cases across industries, building on Week 1’s overview, Week 2’s key features, Week 3’s architecture, Week 4’s interface navigation, Week 5’s licenses, Week 6’s comparison with other BI tools, Week 7’s SAP Cloud Platform integration, Week 8’s story creation, and Week 9’s security and data privacy. It concludes Course 1 by demonstrating SAC’s practical applications.

Background Information: SAC’s unified platform supports diverse industry needs:

• Retail: Use Case: Sales performance tracking and demand forecasting. Features: Dashboards for sales by region/product, predictive analytics for inventory planning. Example: Visualize sales trends, forecast demand using Smart Predict.
• Finance: Use Case: Budget planning and financial reporting. Features: Collaborative planning models, real-time reporting from S/4HANA. Example: Create budgets, track actuals vs. forecasts.
• Manufacturing: Use Case: Supply chain optimization and production analytics. Features: Real-time KPIs, predictive maintenance insights. Example: Monitor production efficiency, predict equipment failures.
• Healthcare: Use Case: Patient care analytics and resource planning. Features: Dashboards for patient outcomes, planning for staff allocation. Example: Analyze bed occupancy, plan staffing needs.
• Public Sector: Use Case: Budget allocation and program performance. Features: Secure reporting, planning for public funds. Example: Track program spending, ensure compliance.
• Key Benefits: Unified BI, planning, and predictive analytics reduce tool fragmentation. Native SAP integration (e.g., S/4HANA, BW/4HANA) for seamless data flows. Secure, compliant environment (GDPR, CCPA) for sensitive data.
• Challenges: Tailoring SAC to non-SAP data environments. Managing costs for large-scale industry deployments. Trial limitations may restrict advanced features (e.g., live connections).

Hands-On Example: Scenario: You’re a business analyst for a retail company using SAC to track and analyze sales performance. Using the SAC trial, you’ll create a retail sales story with visualizations, filters, and predictive insights, simulating a real-world retail use case while applying security and integration concepts from prior weeks.

• Prerequisites: Active SAC trial account (set up in Week 1; access via https://<tenant>.sapanalytics.cloud/). Familiarity with SAC’s interface and features (from Weeks 1–9). Sample dataset: Use SAC’s preloaded “BestRunJuice_SampleModel” or equivalent sales model (simulating retail data). Modern browser (e.g., Chrome, Edge) and internet connection.
• Step-by-Step Instructions: Access the SAC Trial Environment: Log in to your SAC trial account (https://<tenant>.sapanalytics.cloud/). Verify the home page loads with options like “Home,” “Files,” “Create,” and “Browse.” Navigate to “Files” > “Samples” to confirm access to “BestRunJuice_SampleModel” (simulating retail sales data). Create a Retail Sales Story: From “Create” > “Story” > “Canvas” mode. Add a data source: Click “Add Data” > “Data from a Model.” Select “BestRunJuice_SampleModel.” Set up the story: Add a title: “Retail Sales Dashboard.” Add Visualizations: Bar Chart: Drag “Sales Revenue” to Y-axis, “Region” to X-axis. Geo Map: Drag “Sales Revenue” to Size, “Store” to Location. Table: Add columns for “Product,” “Sales Revenue.” KPI Tile: Add for total “Sales Revenue.” Add Filters and Input Controls: Add filter for “Time.” Add input control for “Product.” Incorporate Predictive Analytics: Use Smart Insights on charts. Create a forecast with Smart Predict. Apply Security and Integration Concepts: Secure the story in a folder. Simulate SAP integration. Validate and Troubleshoot: Confirm story functionality. Output: A complete retail story demonstrating SAC’s capabilities.
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