Library › Book 15 › GROUP BY and Aggregation -- Seeing the Big Picture
GROUP BY and Aggregation -- Seeing the Big Picture
4.1🔒Understanding GROUP BYGROUP BY collapses rows into groups. Instead of seeing every individual row, you see one row per group. This is essential for understanding…
4.2🔒Aggregate Functions
4.3🔒HAVING -- Filtering GroupsWHERE filters individual rows before grouping. HAVING filters groups after aggregation.
4.4🔒Detecting DuplicatesDuplicate detection is one of the most valuable GROUP BY patterns for QA:
4.5🔒Error Analysis QueriesThese queries are invaluable during incident investigation:
4.6🔒Business Metrics VerificationUse GROUP BY to verify that business metrics displayed in the UI match the database reality:
4.7🔒DATE_TRUNC for Time-Based AnalysisDATE_TRUNC is a PostgreSQL function that truncates a timestamp to a specified precision:
4.8🔒Practice Schema 4: Error Logging
4.9🔒ExercisesBeginner:
4.10🔒Q&AResume phrasing- Built aggregation-based data quality queries using GROUP BY, HAVING, and DATE_TRUNC to detect duplicate records and anomalous patterns…
4.11🔒Q&ACover letter framingAggregation queries are how I turn raw data into actionable intelligence. Whether it is detecting duplicate records that indicate a…
4.12🔒Q&AInterview framing"I approach data analysis by starting with the question: what does the distribution look like? GROUP BY with COUNT, SUM, and AVG gives me…
4.13🔒Q&AWhat not to say- "I use WHERE to filter aggregated results." -- This confuses WHERE and HAVING, which is a fundamental SQL misunderstanding. - "I do not…
4.14🔒Q&AQuestion 1Prompt: Your e-commerce platform processed 10,000 orders yesterday, but the finance team says the revenue report shows a number that is…
4.15🔒Q&AQuestion 2Prompt: You suspect there is a double-submission bug in your checkout flow. Users might be accidentally creating duplicate orders when they…
4.16🔒Q&AQuestion 3Prompt: Your monitoring shows that the error rate for the /api/checkout endpoint spiked from 0.5% to 8% between 2:00 AM and 3:00 AM last…