Study guide · 8 topics

SQL Exam Study Guide

Eight topic guides covering everything tested on SQL exams and data interviews. Code examples, exam traps, and tips throughout.

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01 · 5 min read

SQL SELECT Explained — WHERE, ORDER BY, LIMIT & DISTINCT

SELECT is the foundation of SQL. Here's what exams test — filtering, sorting, and the operators that trip people up.

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02 · 7 min read

SQL JOINs Explained — INNER, LEFT, RIGHT, FULL OUTER with Examples

JOINs are the most-tested SQL topic. Here's a clear breakdown of every join type with examples you can run.

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03 · 5 min read

SQL GROUP BY & Aggregates — COUNT, SUM, AVG, HAVING Explained

Aggregation is tested in every SQL interview. Here's what you need to know — GROUP BY, HAVING, and the WHERE vs HAVING trap.

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04 · 6 min read

SQL Subqueries Explained — Correlated, EXISTS, IN with Examples

Subqueries unlock powerful data retrieval patterns. Here's what SQL exams test — correlated vs non-correlated, EXISTS, and IN.

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05 · 7 min read

SQL Window Functions Explained — RANK, ROW_NUMBER, LEAD & LAG (With Practice Quiz)

Window functions are the most powerful — and most-tested — advanced SQL feature. Here's everything you need to know.

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06 · 5 min read

SQL Indexes Explained — Types, When to Use, and Query Performance

Indexes are the key to query performance. Here's what interviews test — types of indexes, when they help, and when they don't.

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07 · 6 min read

SQL Transactions Explained — ACID Properties and Isolation Levels

Transactions ensure data integrity. Here's what senior SQL interviews ask — ACID, isolation levels, and concurrency problems.

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08 · 5 min read

SQL String & Date Functions — CONCAT, TRIM, DATE_TRUNC & More

String and date manipulation appears in almost every SQL exam. Here's the functions you need to know.

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Where SQL leads

Certifications that build on SQL

Real proctored exams with published blueprints — each with a free readiness test here that scores you per exam domain rather than giving you one number.

Microsoft AI-103 (Azure AI Apps & Agents)

AI-103’s information extraction domain is retrieval and indexing: semantic, hybrid and vector search for grounding. Querying for the right rows is the skill underneath.

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