Product Sales Analysis I
A easy-tier problem at 85% community acceptance, tagged with Database. Reported in interviews at Ripple and 1 others.
Product Sales Analysis I is an easy database problem that Ripple and Cognizant have actually asked in their assessments. With an acceptance rate above 84%, it looks like a gimme, but the trap is thinking you can wing a SQL query without understanding the join structure. You're aggregating sales data across products and dates, and missing one condition or grouping clause tanks your result set. This is the kind of problem where you blank on the exact syntax during screen share and lose 10 minutes to a stupid mistake. StealthCoder runs invisible during the live OA and surfaces a working solution in seconds if you hit that wall.
Companies that ask "Product Sales Analysis I"
Product Sales Analysis I is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Built by an Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code.
Get StealthCoderThe problem requires joining sales and product tables, then aggregating revenue by product with date filtering. Most candidates default to a LEFT JOIN when an INNER JOIN is correct, or forget to GROUP BY the product identifier entirely and end up with duplicates or rollups. The trick isn't algorithmic; it's mechanical SQL accuracy. You need to select the right columns (product name, year, and summed price times quantity), apply WHERE conditions without breaking the aggregate logic, and order by the correct field. Candidates who've drilled window functions or complex CTEs often overcomplicate this. The real edge is a clean, minimal query that passes all edge cases on the first submission. If you haven't written databases in a week and the syntax slips, StealthCoder handles it during the assessment so you don't spend time debugging.
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Product Sales Analysis I recycles across companies for a reason. It's easy-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Built by an Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Product Sales Analysis I interview FAQ
Is Product Sales Analysis I actually easy or is the acceptance rate misleading?+
The 84% acceptance rate is genuine. It's easy because the logic is straightforward: join and aggregate. The slip-ups happen in execution: wrong join type, missing GROUP BY, or incorrect column selection. If you know SQL fundamentals, you'll pass. It's not a trick problem.
Will Ripple and Cognizant definitely ask this exact problem?+
Ripple and Cognizant have both asked database problems in this difficulty range. This exact problem title may appear, or variations on the same pattern. Either way, understanding joins and aggregation covers it.
What's the most common mistake candidates make on this problem?+
Forgetting to GROUP BY after aggregation, or using a LEFT JOIN when INNER JOIN is required. The second most common: selecting the wrong column for the final result set. Test your GROUP BY logic before submitting.
How does this problem relate to real database work?+
It's a direct copy of real BI queries: pull revenue by product over a date range. The pattern repeats in almost every data analyst role. Master this and you'll recognize the structure in harder problems.
Should I study window functions for this problem?+
No. Window functions are overkill here. GROUP BY with simple aggregates (SUM, COUNT) is the intended solution. Overengineering adds syntax risk for zero gain.
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