---
title: "aggregation"
description: "Aggregation refers to the process of combining multiple individual data values into a single summary value."
canonical: "https://motherduck.com/glossary/aggregation/"
related:
  - title: "Aggregate functions | MotherDuck Docs"
    url: "https://motherduck.com/docs/sql-reference/duckdb-sql-reference/aggregate-functions/"
  - title: "Why Use DuckDB for Analytics?"
    url: "https://motherduck.com/blog/six-reasons-duckdb-slaps/"
  - title: "DuckDB SQL | MotherDuck Docs"
    url: "https://motherduck.com/docs/sql-reference/duckdb-sql-reference/"
---

# aggregation

> Aggregation refers to the process of combining multiple individual data values into a single summary value.

## Overview
Aggregation refers to the process of combining multiple individual data values into a single summary value. In data analysis, aggregation helps compress detailed data into meaningful statistics that provide insights about groups of records rather than individual rows.

## Common SQL Aggregations
The most frequently used SQL aggregation functions include:
- `COUNT()` which tallies the number of rows or values
- `SUM()` which adds numeric values together 
- `AVG()` which calculates the arithmetic mean
- `MIN()` and `MAX()` which find extreme values
- `STDDEV()` and `VARIANCE()` which compute statistical measures of spread

## DuckDB Examples
DuckDB supports standard SQL aggregations plus additional statistical functions. Here are some examples:

Basic aggregation:
```sql
SELECT 
  department,
  COUNT(*) as employee_count,
  AVG(salary) as avg_salary,
  MAX(hire_date) as most_recent_hire
FROM employees
GROUP BY department;
```

Multiple aggregations on the same column:
```sql
SELECT
  MIN(price) as lowest_price,
  MAX(price) as highest_price,
  AVG(price) as avg_price,
  STDDEV(price) as price_stddev
FROM products;
```

DuckDB also supports statistical aggregations like `CORRELATION`, `ENTROPY`, and `SKEWNESS`:
```sql
SELECT
  CORRELATION(price, quantity) as price_qty_correlation,
  ENTROPY(category) as category_entropy,
  SKEWNESS(price) as price_skewness
FROM sales;
```

## Window Function Aggregation
Aggregations can also be used as window functions in DuckDB to compute running totals and moving averages:

```sql
SELECT
  date,
  amount,
  SUM(amount) OVER (ORDER BY date) as running_total,
  AVG(amount) OVER (
    ORDER BY date 
    ROWS BETWEEN 6 PRECEDING AND CURRENT ROW
  ) as seven_day_average
FROM daily_sales;
```

## Filtered Aggregation 
DuckDB supports filtering rows within aggregation functions using the `FILTER` clause:

```sql
SELECT
  COUNT(*) as total_orders,
  COUNT(*) FILTER (WHERE status = 'completed') as completed_orders,
  SUM(amount) FILTER (WHERE status = 'completed') as completed_amount
FROM orders;
```