Descriptive and Predictive Analytics

Descriptive Analytics deals with looking at past data and describing the events and instances which happened. If we expand a little further, Diagnostic Analytics explains “why” something happened. It’s part of data scientist’s day-to-day work. Diagnostic Analytics focuses on the past to find cause-and-effect relationships..

Examples

• Which areas in the world did a particular book sell the most based on sales data?

• Which country’s economy grew the most in the past year?

• Why do cars in traffic follow a certain route the most?

Predictive Analytics is about predicting and forecasting what can happen in the future based on past and the present data. We also have prescriptive analytics. It helps decide which decisions to make to alter the outcome of future events. This is also part of a data scientist’s day-to-day work. Prescriptive analytics focuses on the future to decide which choices will have the best outcome for the company..

Examples

• What will the weather be next week based on previous weather data?

• Where will a wildfire occur before it actually happens?

• Where is a crime about to happen?