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Phase 4 · SQL & Data Engineering Basics

Topics

Data Warehouses (Concept)

Part of the AI Engineer Roadmap.

Summary

Centralized, structured stores (Snowflake, BigQuery, Redshift) optimized for analytical queries across large historical datasets — where training data often lives at scale.

How to Learn This

  • 1Learn the difference between a data warehouse, data lake and database at a conceptual level.
  • 2Read documentation for one warehouse (e.g. BigQuery) to see how querying at scale works.
  • 3Understand columnar storage and why it's fast for analytical queries.

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Batch vs Streaming Data

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Airflow Basics (Overview)

More topics in SQL & Data Engineering Basics

SQL Basics (SELECT, JOIN, GROUP BY)Working with Databases in PythonData Pipelines (Concept)ETL vs ELTBatch vs Streaming DataAirflow Basics (Overview)Working with APIs for Data CollectionWeb Scraping (BeautifulSoup)
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