Which type of data analytics focuses on historical patterns and trends?

Descriptive analytics is focused on analyzing and interpreting historical data to identify trends, patterns, and insights that can be derived from past events. This type of analytics provides a summary of what has happened in a business or system over a specified period, allowing it to produce meaningful reports and visualizations that help stakeholders understand the performance of various metrics.

This includes techniques such as data aggregation and mining, which aim to generate insights related to past behaviors. By evaluating historical data, organizations can make informed decisions and establish benchmarks for future performance.

In contrast, predictive analytics uses historical data to forecast future outcomes, while prescriptive analytics recommends actions based on the analysis of data. Diagnostic analytics goes a step further by investigating the reasons behind past trends or events but does not primarily focus on summarizing historical patterns in the same way that descriptive analytics does. Understanding these nuances allows businesses to select the right analytics approach depending on their goals and the nature of their inquiries.