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How Predictive Analytics evolved

Predictive Analytics

Analytics took its baby steps during the days when excel sheets were developed using existing data. This analytics was cumulative and required sufficient data capture in order to produce insightful results. Cumulative analytics was awfully slow for growing enterprises. But business analytics really took off with the arrival of technologies like Big Data, and Cloud storage. Let’s take a brief journey across Predictive Analytics’ evolution in business:

1. Data Warehouses led to the rise of “What” and “Why” analytics:

Team Sales Funnel Chart

After cumulative analytics failed to bring any significant change in enterprise data analysis, “what” and “why” analytics took over with Descriptive and Diagnostic capabilities. This is when Business Intelligence took shape with the rise of data warehouses. At this point, analytics was mainly reliant on past data and had no means of peeking into the future.

2. Enter “Forecasting”:

When new communication channels opened, mainly social media; data grew massively opening new doors for predicting what the near future would look like according to the closely knit data patterns derived from this “Big Data”. It became simpler to predict the future by comparing trends and insights. “Comparitive Analytics” could predict future trends and tendencies.

3. Predictive Modelling and Visualizations:

Predictive Analytics not only depicts upcoming trends in the form of visualizations but can also adapt to changing trends making it a more accurate method of forecasting the future of business. Predictive Analytics is built on machine learning and statistical analyses and puts massive data chunks to good use, in order to drive businesses forward.


If you’re wondering what Predicitve Analytics’ successor will be like, it may already be here. Yes, Prescriptive Analytics is set to take over from Predicitive Analytics; a more intelligent decision-making guide that is said to suggest ‘best-course-of-actions’ for business decision makers.