SQL for Data Analysis Questions
Using SQL as a tool for data analysis and reporting. Focuses on writing queries to extract metrics, perform aggregations, join disparate data sources, use subqueries and window functions for trends and rankings, and prepare data for dashboards and reports. Includes best practices for reproducible analytical queries, handling time series and date arithmetic, basic query optimization considerations for analytic workloads, and when to use SQL versus built in reporting tools in analytics platforms.
HardSystem Design
0 practiced
Design a SQL-based incremental ETL pattern to populate a daily summary table `daily_revenue(day DATE, revenue DECIMAL)` from a streaming `events` table. Include handling late-arriving events, idempotency, how to perform backfills, and how to schedule updates. Explain SQL examples for incremental upsert (merge) logic.
MediumTechnical
0 practiced
Write an SQL query to compute month-over-month growth (%) in revenue for the past 12 months. Given `orders(order_date DATE, total_amount DECIMAL)`, return `month` (YYYY-MM), `revenue`, `mo_movement_pct`. Use ANSI SQL and handle months with zero revenue.
EasyTechnical
0 practiced
Explain, in plain terms, the difference between INNER JOIN, LEFT JOIN and CROSS JOIN. For each, give a short real-world data-analytics example of when you'd use it (e.g., joining customers to orders).
EasyTechnical
0 practiced
Explain when you would use SQL for analysis versus using built-in functions in a reporting tool (e.g., Tableau, Power BI). Provide examples of tasks best done in SQL and tasks better in the BI tool, considering maintainability, performance, and collaboration.
EasyTechnical
0 practiced
Write a short SQL snippet (ANSI) to pivot monthly sales into columns for `month_1`, `month_2`, `month_3` showing sales for the last 3 months for each product. Given `sales(product_id, sale_date DATE, amount)`, output product_id and three columns. Explain portability limitations across SQL dialects.
Unlock Full Question Bank
Get access to hundreds of SQL for Data Analysis interview questions and detailed answers.
Sign in to ContinueJoin thousands of developers preparing for their dream job.