Lessons

1SQL mental model: grain, order, nulls48 min read

Execution order, grain discipline, bag vs set, three-valued logic, and the narration OS interviewers grade before fancy windows.

  • →SQL Reasoning and Debugging
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2Joins & nulls under interview pressure48 min read

INNER/LEFT/FULL/CROSS, semi and anti joins, ON vs WHERE, null keys, chasm traps, and existence patterns that avoid fan-out.

  • →Joins and Row Sets
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3Aggregations & metric definitions48 min read

GROUP BY discipline, FILTER/CASE aggregates, distinct metrics, weighted ratios, ROLLUP awareness, and date spines.

  • →Reliable Aggregations
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4Window functions & framing50 min read

ROW_NUMBER/RANK, LAG/LEAD, running totals, ROWS vs RANGE traps, QUALIFY, sessionization sketch, top-N per group.

  • →Window Analysis
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5CTEs, recursion & SQL debugging48 min read

Staged CTE style, materialization caveats, recursive hierarchies, fan-out detectors, broken-query clinic, EXPLAIN altitude.

  • →SQL Reasoning and Debugging
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6OLTP schema design interviews50 min read

Keys, normalization vs denorm, N:M bridges, soft delete, multi-tenant pool indexes, money types, and a worked trips schema.

  • →Transactional Schema Design
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7Warehouse facts, dims & events50 min read

Star schema, additive vs semi-additive measures, SCD2 point-in-time, funnels, conformed dims, partitioning and incremental loads.

  • →Analytics Modeling
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8Capstone: live SQL + modeling mock55 min read

Integrated marketplace mock: monthly GMV/buyers, first vs repeat, top category windows, refunds schema, warehouse grains, and a six-axis hire rubric.

  • →SQL Reasoning and Debugging
  • →Window Analysis
  • →Analytics Modeling
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Skills in this course

  1. 01SQL Reasoning and DebuggingState grain, execution order, NULL behavior, and debug complex queries methodically.
  2. 02Joins and Row SetsChoose joins, semi-joins, anti-joins, and keys without fan-out or NULL mistakes.
  3. 03Reliable AggregationsBuild counts, ratios, time buckets, and grouped metrics at a clear grain.
  4. 04Window AnalysisUse ranking, lag, running metrics, and explicit frames correctly.
  5. 05Transactional Schema DesignModel identity, cardinality, history, tenancy, and indexes from access paths.
  6. 06Analytics ModelingDesign facts, dimensions, measures, history, events, and incremental loads.