Top SQL Queries for Data Scientists
Article by Nate Rosidi explains why SQL remains essential for data scientists and presents core SQL concepts and examples. It walks through querying and filtering, NULL handling, data type conversion, aggregation, date/time functions, text manipulation, ranking, window functions, and subqueries/CTEs, with practical snippets drawn from platforms like [[StrataScratch]] and [[LeetCode]] and SQL dialects such as [[PostgreSQL]]. The piece includes business examples—finding best-selling products and calculating moving averages—to show how these techniques combine in real analytics workflows, and highlights common functions (COUNT, SUM, AVG), window and aggregate patterns, and date/text functions. It targets practitioners preparing for interviews and professionals seeking database-centric ways to clean, summarize, and report on large datasets.