"Evidence.dev: Analytics Reports as Code with SQL, Markdown, and CI"
Analytics is too important to live in brittle dashboards and unreviewed point-and-click tooling. This book is for experienced data practitioners—analytics engineers, data platform engineers, and senior analysts—who want the rigor of software engineering applied to reporting: reproducible builds, reviewable diffs, deterministic environments, and secure publishing pipelines. If you've ever shipped a metric only to lose trust in it later, Evidence.dev offers a code-native way to make analytical truth auditable and durable.
You'll learn an end-to-end workflow for "reports as code": structuring an Evidence repo for scale, authoring narrative-first pages in Markdown/Markdoc, embedding and composing named SQL queries as stable data contracts, and shaping datasets for charts, tables, and interactive controls. The book dives into engine-aware SQL design, safe parameterization and templating, caching and extraction strategies, and performance engineering for responsive UX. It also treats delivery as a first-class concern—CI checks, PR previews, environment promotion, secrets handling, governance, and migration practices for long-lived report codebases.
Prerequisites: strong SQL, Git fluency, and comfort with CI/CD concepts. The differentiator is operational depth: not just how to build Evidence pages, but how to run an analytics site like a production system—testable, observable, secure, and maintainable under constant change.
