What distinguishes descriptive analytics from predictive analytics?

Descriptive analytics is primarily focused on summarizing historical data to identify trends, patterns, and insights from past events. This aspect involves interpreting what has happened in the organization, often through metrics and reports that outline performance over time. It helps businesses understand their past performance and provides a foundational understanding of data before diving into more complex analyses.

This distinction is crucial because descriptive analytics lays the groundwork for further analysis, including predictive analytics, which not only relies on historical data but also utilizes that data to make informed guesses about future events. In this way, descriptive analytics captures the essence of what has occurred, effectively conveying a narrative of past performance, which is essential for making strategic decisions.

Predictive analytics, on the other hand, uses the insights gleaned from descriptive analytics to forecast future scenarios based on historical data, but it does not summarize that data in the same manner. Thus, the clarity provided by descriptive analytics as a retrospective look distinguishes it fundamentally from the forward-looking nature of predictive analytics.