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Write Basic Aggregation Queries
GROUP BY, HAVING, and ORDER BY on a sales table.
Window Functions for Ranking & Trends
ROW_NUMBER, LAG, and running totals on a time-series dataset.
Optimize a Slow Query on a 50M-Row Table
Rewrite a query, add indexes, and explain the EXPLAIN plan.
SQL Data Querying, Joins & Advanced Aggregations
SQL is the foundational language for data extraction and business analytics. Hiring managers evaluate data analysts on writing multi-table JOINs, GROUP BY aggregations, CTEs (Common Table Expressions), subqueries, and window functions (ROW_NUMBER(), RANK(), LAG()) to answer real business questions accurately.
1. Relational SQL Query Library
Structured SQL script file containing multi-table JOINs, aggregation metrics, and CTE queries.
2. Query Performance & Execution Analysis
Execution plan breakdown explaining index usage, JOIN optimization, and subquery refactoring.
3. Executive Data Insights Summary
Business report translating raw SQL metric results into actionable stakeholder recommendations.
Frequently Asked Questions (SQL Querying & Analysis)
What is the difference between WHERE and HAVING in SQL?
WHERE filters rows before aggregations are processed, whereas HAVING filters aggregate results after GROUP BY execution.
When should you use Window Functions over GROUP BY?
GROUP BY collapses multiple rows into a single summary row, while Window Functions calculate metrics (like running totals or lead/lag values) across row partitions without reducing the overall row count.
How do you prevent duplicate rows during multi-table LEFT JOINs?
Ensure the joined key has a unique constraint, or use subqueries/CTEs to pre-aggregate the joined table before performing the main JOIN operation.
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