Filtering, Sorting and Aggregating Data in SQL in Data Analyst
This topic becomes much easier when we connect the concept to a real business problem instead of memorizing definitions.
Chapter Overview
Once you can select rows, the next skill is summarizing them. Analysts often need totals, averages, counts, and grouped comparisons. This is where aggregation becomes important.
Core Concepts
GROUP BY collects rows into categories. Functions like COUNT(), SUM(), AVG(), MIN(), and MAX() then summarize each group. HAVING filters grouped results.
SQL Example
SELECT region, COUNT(*) AS total_orders, SUM(revenue) AS total_revenue
FROM orders
GROUP BY region
HAVING SUM(revenue) > 50000
ORDER BY total_revenue DESC;Why It Matters
This type of query appears in sales reporting, finance summaries, and product analysis. It is one of the most practical SQL patterns for analyst interviews and jobs.
Key Takeaways
- Use WHERE, GROUP BY, HAVING, and ORDER BY to explore patterns.
- This chapter belongs to SQL for Data Analysts and is written in a simple student-friendly style.
- Practice with SQL queries with simple table examples to build confidence faster.
