Wow! eBook
Presto SQL for Business Analytics: A Practitioner's Guide from Query to Production
Author(s): SHANE SHANE (Author)
- Publication Date: September 19, 2026
- Language: English
- Print length: 141 pages
- ISBN-10: B0HKDSBNSF
Book Description
The SQL book for analysts who work at scale.Most SQL books teach the database of thirty years ago: a single server, hand-tuned indexes, primary keys enforced up front. The SQL analysts write today runs on distributed engines like Presto and Trino — no primary keys, no indexes, terabytes spread across thousands of files. These engines won't stop you from writing a bad join. They'll run it, expensively, and hand you the bill.Presto SQL for Business Analytics takes you from correct queries to reliable analytical systems. Written for analysts with about a year of SQL experience, it builds the judgment that decides whether a query succeeds at scale: grain, windows, nested data, approximate statistics, performance, and production validation.What you'll learn- Foundations that prevent expensive mistakes — execution order, join fan-out, NULL semantics, deduplication, latest-row selection- Analytical patterns you'll reuse every week — window functions, time series, pivots, grouping sets, gaps-and-islands- Nested and semi-structured data — arrays, maps, structs, and JSON without accidental row multiplication- Dimensional modeling — staging, dimensions, facts, and dashboard tables that don't drift from the truth- Performance engineering — partitioning, skew diagnosis, reading query plans- Production validation — checksum comparisons, reconciliation funnels, and data-quality checks that catch bad deploysEvery example is self-contained with inline sample data: run it as printed, then adapt it to your own tables. Includes 30 exercises with a complete answer key, plus a guide to running everything free with Trino in Docker.SHANE has spent 20+ years building data systems at leading financial and technology companies, writing SQL against data at every scale from gigabytes to petabytes. These are the patterns that survived contact with production.
