<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>The Practice of Data</title><description>Practical lessons on ingesting, modeling, and reporting on data, for data analysts, engineers, and leaders.</description><link>https://practiceofdata.com/</link><item><title>[Free Github Repo] An End-to-End Data Stack on Your Computer</title><link>https://practiceofdata.com/blog/end-to-end-data-stack/</link><guid isPermaLink="true">https://practiceofdata.com/blog/end-to-end-data-stack/</guid><description>A fictional e-commerce company, six tables, and four tools wired together — Faker, DuckDB, dbt, and Dagster. Clone it, run one command, and get a tested analytics warehouse running locally.</description><pubDate>Wed, 08 Jul 2026 00:00:00 GMT</pubDate><category>Pipelines &amp; Orchestration</category><category>SQL &amp; Data Modeling</category></item><item><title>A practical guide to structuring dbt models: staging, intermediate, marts</title><link>https://practiceofdata.com/blog/dbt-data-modeling-layers/</link><guid isPermaLink="true">https://practiceofdata.com/blog/dbt-data-modeling-layers/</guid><description>How to organize a dbt project so new team members can find what they need in seconds, not hours. A layer-by-layer breakdown with naming conventions you can copy today.</description><pubDate>Mon, 06 Jul 2026 00:00:00 GMT</pubDate><category>SQL &amp; Data Modeling</category></item><item><title>Airflow DAG patterns that keep pipelines maintainable as they grow</title><link>https://practiceofdata.com/blog/airflow-dag-patterns/</link><guid isPermaLink="true">https://practiceofdata.com/blog/airflow-dag-patterns/</guid><description>Task granularity, sensor timeouts, and idempotency rules that stop a 10-task DAG from turning into an unmaintainable 200-task mess a year later.</description><pubDate>Mon, 29 Jun 2026 00:00:00 GMT</pubDate><category>Pipelines &amp; Orchestration</category></item><item><title>Data quality testing 101: the four tests to add before anything else</title><link>https://practiceofdata.com/blog/data-quality-testing-basics/</link><guid isPermaLink="true">https://practiceofdata.com/blog/data-quality-testing-basics/</guid><description>You don&apos;t need a full data observability platform to catch most data quality issues. Four test types, applied consistently, catch the vast majority of real incidents.</description><pubDate>Mon, 15 Jun 2026 00:00:00 GMT</pubDate><category>Data Quality &amp; Testing</category></item><item><title>What actually matters in your first year as a data engineer</title><link>https://practiceofdata.com/blog/career-advice-beginner-data-engineers/</link><guid isPermaLink="true">https://practiceofdata.com/blog/career-advice-beginner-data-engineers/</guid><description>Less time memorizing tool syntax, more time on the three skills that separate a junior data engineer from a senior one — and that nobody tells you about in a bootcamp.</description><pubDate>Mon, 01 Jun 2026 00:00:00 GMT</pubDate><category>Career Advice</category></item></channel></rss>