Question 1

What industries do the datasets cover?

Accepted Answer

There are 15 real-world industry datasets: AdTech, Banking, Fintech Trading, Health Claims, Lodging, Logistics, Food Delivery, Ride-Hailing, Payments, Real Estate, Retail, SaaS B2B, Social Graph, Streaming Media, and Telecom ISP. Each dataset has realistic schemas modeled after companies in that industry.

Question 2

Are these real company datasets?

Accepted Answer

The datasets are realistic simulations modeled after real industry domains. Each problem is framed as a business scenario at a specific company — for example, analyzing churn at Netflix-style streaming data, or optimizing delivery routes with logistics data similar to FedEx or UPS.

Question 3

Can I practice both SQL and Python on the same dataset?

Accepted Answer

Yes. Every industry dataset includes both SQL and Python (pandas) problems. SQL problems run on SQLite in your browser, while Python problems use Pyodide (Python WebAssembly). You can practice both languages against the same tables and schemas.

Question 4

How are the problems graded?

Accepted Answer

SQL problems are graded by comparing a SHA-256 hash of your query result against the expected output. Python problems run your solve() function against the full dataset and compare the resulting DataFrame. All grading happens instantly in your browser — no server round-trip needed.

SQL & Python Interview Questions by Industry

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