Descriptive analytics is used to:

Descriptive analytics is primarily focused on summarizing historical data to provide insights into past trends and patterns. This type of analytics involves collecting data from various sources, then analyzing and interpreting that data to generate reports, summaries, and visualizations that offer a clear picture of what has happened in a given timeframe. By leveraging descriptive analytics, organizations can understand outcomes and behaviors based on prior events, which can inform their decision-making processes.

In contrast, analyzing future trends based on predictions relates more to predictive analytics, which utilizes statistical models and machine learning techniques to forecast future events. Creating new data sets is more aligned with processes involved in data generation or data management rather than analytics. Lastly, enhancing data storage solutions pertains to database management and data architecture rather than the analysis of data itself. Therefore, the primary aim of descriptive analytics lies in its ability to summarize and provide insights on historical data for better understanding and informed decision-making.