History Of Predictive Analytics

Predictive analytics encompasses a variety of statistical techniques from data mining, predictive modeling, and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events. A Brief History of Predictive Analytics M oore's law dictates that technology becomes two times faster, and half as expensive, every two years. This is part 1 of a 3-part blog, where we outline the history of Predictive Analytics.

Given it is such a hot topic with our warranty manufacturing clients - as well as just about any company looking to drive higher efficiency, profitability and customer satisfaction - we thought a quick history lesson might be warranted (pun intended). Part 1 takes you from the 1940's - 1950's, Part. However, The history of predictive analytics starts in 1689.

Its true that record keeping standards, relational databases, faster CPUs, and even newer technologies such as Hadoop and MapReduce have made predictive analytics an accessible tool for decision making. However, the history of predictive analytics show that it has been used for centuries. Predictive analytics is used to make forecasts about trends and behavior patterns.

Predictive analytics uses several techniques taken from statistics, data modeling, data mining, artificial intelligence, and machine learning to analyze data in making predictions. Predictive analytics is the use of statistics and modeling techniques to determine future performance based on current and historical data. Here we look back at the evolution of the analytics industry as a whole, from its first iterations as a manual, offline process to today's innovations in predictive decision-making.

Let's begin with the early days of analytics. Here's a detailed overview of the evolution of predictive analytics: Early Beginnings The journey of predictive analytics began with statistical models and probability theory in the early 20th. Predictive analytics includes a diversity of methods from statistics, modelling, machine learning, and data mining that analyse existing and historical data to make predictions about upcoming, or otherwise unknown, events.

Predictive analytics has its origin in the 1940s, when governments started using the first computational models. Predictive analytics is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future.