Which type of data analytics focuses on analysis of past data to understand trends and cause-effect relationships?

The focus of descriptive analytics is on utilizing historical data to gain insights into past events. This type of analysis helps organizations to summarize historical performance and identify patterns over time, which can include trends and relationships that have emerged from the data. By examining what has happened previously, descriptive analytics provides a foundational understanding of data, allowing businesses to recognize behaviors and outcomes based on past performance.

In contrast, predictive analytics aims to forecast future trends based on historical data and patterns, which means it looks ahead rather than focuses solely on understanding the past. Prescriptive analytics goes a step further by not just predicting outcomes but suggesting actions to achieve desired results. Lastly, diagnostic analytics seeks to explain why certain events occurred, analyzing past data to understand the underlying causes of those events, rather than simply summarizing them. Hence, descriptive analytics is the best fit as it directly addresses the analysis of past data to discern trends and relationships.