Knowledge hub
Tutorials, case studies, and notes on analytics engineering and BI.
Column cardinality, not row count, drives Power BI model size. How VertiPaq compression works, why one wide table fights it, how to restructure into a star schema, and which columns to attack first using DAX Studio.
BigQuery bills you for bytes read, not rows returned. A practical guide to partition pruning and the filters that silently defeat it, clustering, pushing filters below joins, pre-aggregation, and finding your real spend in INFORMATION_SCHEMA.
Why iterrows is slow, what actually happens when you cross from a NumPy array into Python objects, and how to replace row loops with boolean masks, np.select, map, merge and groupby transform — plus the cases where a plain loop is still the right answer.
Stop guessing at slow SQL. A practical guide to EXPLAIN ANALYZE: how to read the plan tree, the four numbers that actually matter, why per-loop timings mislead, and why bad row estimates cause more slow queries than missing indexes.
A practical guide to breaking into analytics engineering: the T-shaped skill set to build, the portfolio that actually gets callbacks, and the mistakes that quietly sink most applications.