Power Bi Fact Tables Different Granularity at Natalie Axon blog

Power Bi Fact Tables Different Granularity. The way i see it, there are two options : In your example, copy the dim_geo. Multiple fact tables related to each other with different granularities. 1) load the 10 dimensions + 2 fact tables in power bi and make the star schema. How could i resolve the issue of different granularity between these two fact tables in power bi? Remember that the granularity represents the level of detail in each row of your fact table. What i'm not clear is the correct way to create the schema i.e. The grain of a fact table is the level of details stored in the fact table. How to connect these tables in data. However, the second fact table, in addition to those dimensions, will allow me to slice and dice by promotion and sales territory too. Import the fact table without defining a relationship in the data model, and simulate the relationship (at the product. The first fact table gives me the power to slice and dice data of sales by product, date or customer dimension. Being able to combine data from both fact tables in one visual and compute new measures based on both fact tables. If you have effectively the same dimensional data but at different grains then you handle this by creating aggregate dimensions.

Remember that the granularity represents the level of detail in each row of your fact table. In your example, copy the dim_geo. The grain of a fact table is the level of details stored in the fact table. The first fact table gives me the power to slice and dice data of sales by product, date or customer dimension. How could i resolve the issue of different granularity between these two fact tables in power bi? However, the second fact table, in addition to those dimensions, will allow me to slice and dice by promotion and sales territory too. 1) load the 10 dimensions + 2 fact tables in power bi and make the star schema. Multiple fact tables related to each other with different granularities. What i'm not clear is the correct way to create the schema i.e. If you have effectively the same dimensional data but at different grains then you handle this by creating aggregate dimensions.

Create Lookup Tables from Fact Tables in Power BI Data Science Review

Power Bi Fact Tables Different Granularity If you have effectively the same dimensional data but at different grains then you handle this by creating aggregate dimensions. The way i see it, there are two options : What i'm not clear is the correct way to create the schema i.e. In your example, copy the dim_geo. Import the fact table without defining a relationship in the data model, and simulate the relationship (at the product. The grain of a fact table is the level of details stored in the fact table. However, the second fact table, in addition to those dimensions, will allow me to slice and dice by promotion and sales territory too. The first fact table gives me the power to slice and dice data of sales by product, date or customer dimension. If you have effectively the same dimensional data but at different grains then you handle this by creating aggregate dimensions. How to connect these tables in data. How could i resolve the issue of different granularity between these two fact tables in power bi? Remember that the granularity represents the level of detail in each row of your fact table. 1) load the 10 dimensions + 2 fact tables in power bi and make the star schema. Multiple fact tables related to each other with different granularities. Being able to combine data from both fact tables in one visual and compute new measures based on both fact tables.