Capital One·Data Analyst·Online Assessment (OA)·Intermediate

Intermediate

May 2026

Summary

Capital One data analyst SQL question, one problem, conditional aggregation with a twist. Pretty clean setup but the logic tripped me up more than I expected.

Questions Asked (1)

Given a products table and a purchases table, return the minimum purchase price per product category, but only if that category has at least one purchase rated above 4 stars. If no such purchase exists for a category, return 0 instead.

Data ModelingProduct Analytics & Metrics

Author's notes

The conditional part is what got me.

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AI HintsAI Generated

Suggested Approach

Join the products and purchases tables, then use conditional aggregation to compute the minimum purchase price per category while checking for the presence of a rating above 4 stars. Leverage CASE expressions inside aggregate functions or a HAVING clause combined with COALESCE/NULLIF to return 0 when the condition is not met. This approach keeps the logic in a single, readable query without requiring multiple subqueries.

Pro tip: Using CASE WHEN inside MIN() — e.g., MIN(CASE WHEN rating > 4 THEN price END) — elegantly handles the conditional minimum in one pass, but remember to wrap it with COALESCE(..., 0) to replace NULLs with 0, which directly mirrors the business requirement and signals strong SQL fluency to the interviewer.

1. Clarify the Schema & Requirements

Identify the key columns in both tables (e.g., product_id, category, price in products; purchase_id, product_id, rating, price in purchases) and confirm the exact definition of 'purchase price' — is it stored in the purchases or products table? Clarifying ambiguities upfront demonstrates analytical rigor.

2. Join the Tables

Perform an INNER or LEFT JOIN between the purchases and products tables on product_id to bring category information alongside purchase-level data. Choose the join type based on whether you need to account for products with no purchases.

3. Apply Conditional Aggregation

Use COALESCE(MIN(CASE WHEN rating > 4 THEN price END), 0) grouped by category to compute the minimum price only among purchases rated above 4 stars, defaulting to 0 if no such purchase exists in that category.

4. Group and Filter Results

Add a GROUP BY category clause to aggregate results at the category level. Avoid using a HAVING clause to filter out categories here, since the requirement is to return 0 rather than exclude categories — a subtle but important distinction.

5. Validate & Optimize

Mentally test edge cases: categories with all ratings ≤ 4 (should return 0), categories with no purchases (handle via LEFT JOIN if needed), and ties in minimum price. Mention indexing on product_id and category for performance in a large-scale environment like Capital One.

Key Points to Mention

Conditional aggregation using CASE WHEN inside MIN() to filter rows within an aggregate without a subquery
COALESCE to convert NULL aggregation results into 0, directly satisfying the business rule
The distinction between using HAVING (which excludes groups) vs. COALESCE (which returns 0) — choosing the correct approach for the stated requirement
JOIN strategy selection (INNER vs. LEFT JOIN) depending on whether categories with zero purchases should appear in the output
Grouping by category to produce one row per category in the final result set
Performance considerations such as indexing on join keys and category columns, relevant for Capital One's large transaction datasets

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.