Advanced Aggregations

In today’s dynamic retail environment, we often need to summarize data to get both detailed insights and an overall picture. Imagine we are tasked with generating a sales report of OnlineStore that not only shows the total sales for each product but also includes a grand total for all products combined. This is where advanced aggregations shine. 

Let's explore the advanced techniques of data aggregation. We'll aim to:

• Understand why advanced aggregation techniques like WITH ROLLUP are useful.

• Understand how to perform advanced aggregations using WITH ROLLUP.

• Perform grouping with automatic subtotals and grand totals.

Understanding advanced aggregation

Advanced aggregation refers to the advanced techniques we use in SQL to perform complex summarizations of our data. While basic aggregation functions like SUM, AVG, COUNT, MIN, and MAX provide us with overall figures for a group, advanced aggregation allows us to go further by generating additional layers of summary, such as subtotals and grand totals.

We need advanced aggregation as it helps us build comprehensive reports that require not just simple totals but also a detailed breakdown of our data. For instance, in scenarios like sales reporting, it is often essential to see both the totals for individual products and an overall total across all products. Advanced aggregation simplifies our queries by allowing us to derive these multiple levels of insights in a single step, making our data analysis more efficient and informative. Techniques such as WITH ROLLUP or nesting aggregate functions via subqueries are examples of advanced aggregation.

Using WITH ROLLUP

We often need hierarchical summaries in business reports. For example, a breakdown of sales by category, plus an overall total. Without WITH ROLLUP, we would run multiple queries or manually compute the grand total. WITH ROLLUP saves effort by automatically adding these subtotals and the grand total row to our query results.

WITH ROLLUP is an extension to the GROUP BY clause that allows us to generate subtotals and a grand total for our grouped data. This helps when we want to see not only each group’s total but also the overall total in a single result set.

When we use WITH ROLLUP alongside GROUP BY, SQL attempts to compute the normal grouped rows plus additional rows for each level of grouping. The final row (or rows) commonly contains NULL values in grouped columns, representing the grand total, or the subtotal for that grouping level.

In SQL, the syntax of using WITH ROLLUP is as follows: