data-engineer-handbook

GitHub describes it as This is a repo with links to everything you'd ever want to learn about data engineering. The repository metadata lists Jupyter Notebook as its primary language. This article stays within the project description and details documented in the GitHub repository README.

GitHub describes it as This is a repo with links to everything you'd ever want to learn about data engineering. The repository metadata lists Jupyter Notebook as its primary language. The README describes the project this way: If you are new to data engineering, start by following this 2024 breaking into data engineering roadmap

The README section "Getting started" states: For more applied learning: - Check out the projects section for more hands-on examples! - Check out the interviews section for more advice on how to pass data engineering interviews! - Check out the books section for a list of high quality data engineering books - Check out the communities section for a list of high quality data engineering communities to join - Check out the newsletter section to learn via email

The README section "Companies:" states: - Orchestration - Data Lake / Cloud - Data Warehouse - Data Quality - Education Companies - Analytics / Visualization - Data Integration - Semantic Layers - Modern OLAP - LLM application library - Real-Time Data - Data Lineage

The README section "Social Media Accounts" states: Here's the mostly comprehensive list of data engineering creators: (You have to have at least 5k followers somewhere to be added!)

The repository README is the source for this review. It does not replace a local installation or an independent test.

• Source 1 · Project repository
• Source 2 · README