DE Zoomcamp 4.3.1 - dbt Project Structure скачать в хорошем качестве

DE Zoomcamp 4.3.1 - dbt Project Structure

In this tutorial, you'll learn the anatomy of a dbt project and understand the purpose of each directory and file created when you initialize dbt. By the end of this video, you'll know where to place different types of SQL logic, how to organize your transformations, and understand dbt's recommended project structure conventions. 🔗 Course materials: https://github.com/DataTalksClub/data... 💬 Join the community: https://datatalks.club/slack What You'll Learn: Understanding the dbt_project.yml file and why it's critical for every dbt command Using the analysis folder for data quality reports and administrative queries Creating reusable logic with macros (similar to Python functions) Working with seeds for quick CSV ingestion and lookup tables Implementing snapshots to track slowly changing dimensions Writing singular tests as SQL assertions Organizing models into staging, intermediate, and marts layers Timestamps: 0:00 - Introduction to dbt project structure 0:41 - Analysis folder: SQL scripts for internal use 2:04 - dbt_project.yml: The most important configuration file 3:56 - Macros: Reusable logic and encapsulation 6:13 - Models folder overview (detailed later) 6:26 - README.md: Project documentation and setup guides 7:19 - Seeds: Uploading CSVs and flat files 9:21 - Snapshots: Tracking history of changing columns 11:46 - Tests: SQL assertions and singular tests 14:12 - Models deep dive: Staging, intermediate, and marts 15:07 - Staging layer: Raw sources and minimal cleaning 16:49 - Marts layer: Production-ready tables for end users 18:12 - Intermediate layer: Complex transformations and heavy cleaning 19:12 - Alternative naming conventions and best practices