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Learning SQL, Part 5 - Aggregations and Group By Statements

This is the fifth article in the learning SQL series:

Aggregating in SQL: GROUP BY Statements

Previous articles reviewed how to select relevant records from tables and apply filter conditions as needed. However, many times in reporting you want to aggregate results and perform additional calculations - such as counting the number of rows for a group or adding subtotals. This is where the GROUP BY statement comes in.

For this example, a new table will be used - FactResellerSales - in order to demonstrate how to aggregate sales dollars by date. The table has an OrderDate column that we’d like to see the total ExtendedAmount displayed for each day.

To get the subtotal by days, we’ll use the SUM aggregation function and GROUP BY on OrderDate. The general idea is to aggregate a metric using one of the various aggregation functions available and all the other columns (typically descriptive attributes such as dates, products, etc) will be included in both the select and group by statements.

	,SUM(ExtendedAmount) as [ExtendedAmountTotal]
FROM [AdventureWorksDW2017].[dbo].[FactResellerSales]
Example 1 Query: Sum Aggregations
Example 1 Results
Example 1 Results

Other Aggregate Functions

While SUM is the most commonly used aggregation function, there are many more that can be used. A list of aggregation functions can be viewed on the Microsoft documentation page. Max, Min, Avg, and Count are some of more frequently used functions in addition to Sum.

Next Steps

Try some of the above functions (in addition to Sum) on your own to get a feel for using these. You can even combine with previous concepts - for example COUNT(DISTINCT LastName) from the DimCustomer table will give you a distinct/unique count of customer last names.

Check out additional articles in this series here:

For a deeper dive into some of the concepts related to this article, check out the following books: