Data analytics can be categorized into four main types based on its applications and distinct purposes.
1. Descriptive Analytics
The goal of descriptive analytics is to comprehend historical occurrences and turn data into insightful summaries. A retail business might, for instance, examine sales data to find that overall sales increased by 40% during the most recent quarter. Dashboards and reports are frequently created for this purpose using tools like Tableau or Power BI.
2. Diagnostic Analytics
By finding patterns and connections in data, diagnostic analytics seeks to determine the causes of particular outcomes. For instance, a bank may discover a correlation between increased unemployment in a region and an increase in loan defaults, in which the borrower fails to repay a loan according to the agreed terms.
3. Predictive Analytics
Predictive analytics forecasts future patterns by utilizing statistical models and past data. E-commerce companies, for instance, can use machine learning algorithms like regression or classification to forecast the purchasing habits of their customers.
4.Prescriptive Analytics
Prescriptive analytics takes one step further by integrating data with models and rules to recommend actions to get desired outcomes. For instance, a ride-sharing app may use demand projections and traffic patterns to suggest the best prices during peak hours.
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