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The Practical Data Analyst

The learning path that matches what employers actually ask for. SQL appears in over 80% of data analyst job postings, Excel in 60%, Python in 50%. This is the order to learn them in, why that order works, and the trap that costs most beginners a year.

The lessons

  1. 1

    Part 1 · 8 min

    Window Functions Are SQL's Most Underused Feature. Five Patterns Cover Nearly Everything.

    Five window-function patterns that cover most analytics SQL: dedupe with ROW_NUMBER, top-N per group with RANK, period comparisons with LAG, running totals with explicit frames, bucketing with NTILE. Every query ran and its output is shown; a 200,000-row timing test puts the window function at 0.46s against 5.92s for the equivalent self-join on 5,000 rows.

  2. 2

    Part 2 · 7 min

    Data Storytelling Teaches You to Present a Finding. Nobody Teaches You to Find One.

    Every guide teaches you to present a finding. None teach you to find one. The four questions that do the work, including the one that broke open Google's Sierra Leone trial.

  3. 3

    Part 3 · 8 min

    Most Analytics Bugs Are Data Bugs. Five Checks That Catch Them Before the Meeting.

    Five validation checks every analyst should run before trusting a table: duplicates, NULL key columns, out-of-range values, cross-field arithmetic, orphan references. Tested on a 2,010-row orders table with 50 planted defects; the checks flagged 51 rows, and the misses are as instructive as the catches.