4 Types of Analytics

Data analytics is a spectrum ranging from focusing on what happened in the past (descriptive analytics) to recommending actions to change future results (prescriptive analytics).

These stages also reflect maturity of an organization and the skills of data analysts working with the data.

▶ Descriptive Analytics - What happened?
You can't look into the future without first understanding what happened in the past. At the core, data analytics and business analytics start with capturing what happened in the past.

▶ Diagnostic Analytics - Why did it happen?
Once you establish WHAT happened, you can start to explore the next stage of data analysis - why did it happen? How do different variables interact with each other? Which ones impact others?

▶ Predictive Analytics - What is going to happen?
With predictive analytics, we shift from looking into the past to looking towards the future. Very simple predictive analytics assume that everything in the future is the same as the past. A trend analysis which is forward looking is a basic example of predictive analytics.

▶ Prescriptive Analytics - What should happen?
Ultimately, data analytics is most useful when it takes on a business analytics spin. That is, prescribing or recommending what action should be taken to change the future. Prescriptive analytics builds on predictive analytics and says that if we change input X then we can achieve outcome Y.

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