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Learn Data - Without Chasing a Certification

Plain-English explanations of data engineering, analytics and databases for people who want to understand the work, not just pass an exam.

Built and maintained by Patrick Wiloak - Ex-AWS Solutions Architect, 19x multi cloud certified, 64 certifications and accreditations, 10 years in tech. If certs aren't your goal, start here.

πŸŽ₯ @patrickwiloak | πŸ’Ό LinkedIn


Who this is for

You want to understand data work, but:

  • You're not preparing for an exam (or not yet)
  • You want context and intuition, not 200-question fact dumps
  • You'd rather learn the why before drilling into one vendor's tools
  • You're an analyst, developer, founder, PM, or career changer eyeing a data role

If you do want certifications, head to the Study Hub - every data cert on this site, indexed by provider.


What's in this hub

The path

  • Data from Scratch - eight phases from "what is a table?" to data engineer, analytics engineer or DBA. Each phase lists what to read, what to build, and what you can do once it is done.

Bite-size concept pages

  • Concepts - 10 topic pages, 5-10 min each. SQL vs NoSQL, ETL vs ELT, batch vs streaming, queues vs streams, warehouses vs lakes vs lakehouses, modeling for analytics, file formats and partitioning, pipelines and orchestration, quality and lineage, eventual consistency.

Reference


How to use this

There's no single right order. Pick what fits:

If you want to... Start here
Go from zero to a data job Data from Scratch
Understand one concept (ETL, lakehouse, streaming, ...) Concepts
Look up a term you keep seeing Glossary
See how real data platforms are laid out Architecture patterns
Build a pipeline end to end Build a data pipeline
Compare database services across clouds Database comparison

Before and after this hub

  • Never used a terminal? Start with Day One on Cloud Zero to Hero - terminal, git, HTTP and servers, assuming nothing.
  • Need cloud basics for phase 6? Cloud from Scratch covers compute, storage, networking and identity.
  • Ready for machine learning? AI Zero to Hero picks up where data engineering hands off.

Why this exists

Most data content is either:

  1. Cert-shaped - exam objectives, fact sheets, practice questions (great if you have an exam date, useless if you just want to understand)
  2. Vendor marketing - "unlock the power of your data!" (no actual technical content)
  3. Tool tutorials - click-by-click in one product, with no explanation of why the design looks the way it does

This hub is the missing middle: technical, accurate, plain-English, no exam scaffolding.


Contributing

Spot something wrong, unclear, or missing? See CONTRIBUTING.md. Plain-English contributions especially welcome - if you can explain something better than I did, please do.