What type of analysis is primarily concerned with summarizing historical data?

Descriptive analytics focuses on summarizing and interpreting historical data to understand past events and trends. It involves the use of various statistical measures to present and visualize data, allowing organizations to gain insights into what has happened over a specific time period. This type of analysis typically includes data aggregation and data visualization techniques, such as charts and graphs, to provide a clear and concise summary of the data.

The aim of descriptive analytics is to provide a straightforward summary that helps stakeholders make sense of the data without necessarily delving into the reasons behind it or making predictions about future trends. It lays the foundation for further analysis by giving context to the data, which is essential for decision-making processes.

In contrast, prescriptive analytics goes further by recommending actions based on data, while diagnostic analytics seeks to uncover the causes of past outcomes. Predictive analytics uses historical data to forecast future outcomes based on patterns found in the data. Thus, while all these types of analytics play important roles in data analysis, descriptive analytics specifically addresses the summarization aspect of historical data, making it the correct choice for this question.