Comparing SQL Window Functions vs Aggregation for Data Summarization

When working with SQL, summarizing data is a common task. Two popular approaches to summarize data are using aggregation functions and window functions. Both have their uses and understanding the difference will help you write more efficient and insightful queries.

Aggregation functions group rows and return a single summary value per group, such as total sales per region. On the other hand, window functions compute values across a set of rows related to the current row without collapsing the rows. This means you can keep the original row detail while adding summary information.

Let's consider a sample sales table to illustrate the difference:

CREATE TABLE sales (
  id INT,
  region VARCHAR(50),
  salesperson VARCHAR(50),
  amount DECIMAL(10,2)
);

INSERT INTO sales VALUES
(1, 'North', 'Alice', 100.00),
(2, 'North', 'Bob', 150.00),
(3, 'South', 'Charlie', 200.00),
(4, 'South', 'Alice', 50.00),
(5, 'East', 'Bob', 120.00);

### Using Aggregation If you want to get the total sales per region, you would use the `GROUP BY` with aggregation functions like `SUM()`:

SELECT region, SUM(amount) AS total_sales
FROM sales
GROUP BY region;

This query returns one row per region with the total sales. However, all salesperson details are lost because aggregation collapses rows.

### Using Window Functions If you want to see each sale but also want to add the total sales per region alongside each row, window functions are the answer:

SELECT
  id,
  region,
  salesperson,
  amount,
  SUM(amount) OVER (PARTITION BY region) AS total_region_sales
FROM sales;

Here, the `SUM(amount) OVER (PARTITION BY region)` calculates the total sales per region, but unlike aggregation, it does not group or collapse rows. Each sale is still shown individually with the added total information.

### Summary - Use **aggregation** (`GROUP BY`) when you want to reduce multiple rows into summarized groups. - Use **window functions** when you want to keep row-level detail but also add summary calculations. Understanding when to use each will improve your SQL querying skills and allow you to produce more flexible reports.