A data summarization tool that reorganizes and aggregates data from a larger dataset, grouping values by selected dimensions to reveal patterns and totals.
A pivot table lets you quickly summarize large datasets without writing code. You choose which fields to use as rows, which as columns, and which values to aggregate (sum, count, average). The result is a compact summary table that makes patterns visible at a glance.
Pivot tables are available in spreadsheet applications like Excel and Google Sheets, and equivalent functionality exists in SQL (GROUP BY), Python (pandas pivot_table), and BI tools.
Example: A dataset of 50,000 building permit applications contains columns for year, municipality, permit type, and value. A pivot table with municipality as rows, year as columns, and sum of permit value as the aggregated field produces a compact table showing total permit value by municipality and year — turning 50,000 rows into a 20-row summary.