Aggregation

Aggregation: Collecting and Summarizing Data for Insights

Overview

Aggregation is the process of rolling up many individual data points into a smaller set of summary metrics such as sum, average, minimum, maximum, or count. Instead of looking at every single transaction, you can aggregate by day, by customer, or by channel to see the bigger picture. This is what turns noisy raw data into clean, readable charts and KPIs.

How Aggregation Works

In practice, most dashboards are built on top of aggregated tables or queries. For example, you might aggregate revenue by month to track growth over time, or aggregate support tickets by category to see which issues are most common. Good aggregation choices balance detail and simplicity so stakeholders can answer questions quickly without losing important signal.

Why Aggregation Matters in BI

Aggregation reduces complexity, accelerates query performance, and makes trends easier to see. It powers KPIs, time-series charts, and summary tables across modern BI stacks. Modern BI and AI tools can automatically suggest useful aggregations, helping teams move from spreadsheet exports to repeatable, reliable views of the business.