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Analytics Engineering Resources

A list of tools, concepts, and learning resources for analytics engineers. It covers essential technologies, frameworks, and best practices. While most of the links focus analytics enginnering there's some that are data engineering. Since there's so much overlap between the two fields.

🖥️ Contributing

Feel free to contribute to this list by adding links you've found helpful. Submit a Pull Request (PR) with your suggestions.

⏰ Getting Started


⚒️ Tools & Concepts for Analytics Engineers

Data Transformation

  • dbt – Modular SQL-based transformations
  • SQLMesh – Open source Data Transformations
  • DataForm – Google BigQuery specific Data Transformation tool
  • SQL Basics – Querying and transforming structured data
  • Apache Spark – Large-scale distributed data processing

Orchestration

Data Storage

Version Control & CI/CD

  • Git – Version control for data projects
  • GitHub Actions – Automate testing and deployment

Business Intelligence (BI) Tools

  • Looker – Modern BI platform
  • Metabase - Open source & scalable
  • Power BI - One of the major players, from Microsoft
  • Tableau – The other major player, from/owned by Salesforce

Infrastructure & Deployment

  • Docker – Containerization for data apps
  • Kubernetes – Orchestrate and scale data pipelines
  • Terraform – Infrastructure as code

✏️ Best Practices

⚠️This section is still a work in progress, feel free to add more ⚠️

Data Modeling

  • Use a Star Schema – Organize data into fact and dimension tables to improve query performance.
  • Partition & Cluster Large Tables – Partition by date and cluster by frequently filtered columns to speed up queries.
  • Documentation – Document the data models to keep schema and relationships clear.

📚 Learning Resources

  • Specific Courses
  • Sites to Find Datasets
  • LinkedIn Creators
  • Books
  • Newsletters

Specific Courses

Sites to Find Public Datasets

Note this is very similar to the same section in data-analytics-resources.

LinkedIn Creators

Books

Newsletters

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Resources to learn analytics engineering

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