Descriptive analytics is a data analysis approach that focuses on summarizing and interpreting historical data to understand what has happened in the past. It uses methods such as aggregation, statistical analysis, and data visualization to identify trends, patterns, and anomalies across time periods, departments, or customer segments. This foundational layer of analytics helps organizations answer basic but critical questions like “What happened?”, “When did it happen?”, and “To what extent?”
Common tools used in descriptive analytics include dashboards, reports, pivot tables, and key performance indicators (KPIs). It forms the baseline for more advanced analytics methods, such as diagnostic, predictive, and prescriptive analytics. For data professionals, descriptive analytics is essential for establishing context, reporting performance, and providing stakeholders with clear, visualized summaries of business activity.