AWS Data Lake Foundations
A working data lake is more than three S3 buckets named bronze, silver, and gold. The parts that decide whether the lake actually earns its keep, the catalog strategy, the governance evidence, the access patterns, the cost guardrails, almost never make it into the intro diagrams.
This series walks through the layers and infrastructure decisions that matter once the lake stops being a proof of concept and starts being a real platform.
Who This Is For​
- Data engineers building or operating a lake on AWS
- Platform leads responsible for governance, audit, and trust
- Architects evaluating how to bolt a real governance story onto an existing lake
- MSBA, data science, and analytics students looking at how production lakes are actually structured
What This Series Covers​
Modules will be added as the series grows. The first focuses on a layer most lakes are missing entirely.
| # | Module | What You'll Learn |
|---|---|---|
| 1 | The Governance Data Layer | The S3 bucket that holds the lake's about-the-data evidence, why it matters, and what belongs in it |
More to come:
- Storage layout: bronze, silver, gold, and the patterns that survive contact with real data
- Catalog strategy: Glue vs. open-source catalogs, and where each falls short
- Lake Formation patterns for fine-grained access
- Data product packaging: contracts, SLAs, and the consumer interface
- Cost guardrails: lifecycle, storage class, and query economics
- Lineage and data quality as operational concerns
Prerequisites​
- Basic familiarity with S3, IAM, and Athena
- Some exposure to data engineering concepts (ingestion, ETL, query)
- An AWS account if you want to follow the hands-on parts
How To Use This Series​
Each module is independent enough to read on its own. If you're standing up a new lake, work through them in order. If you're hardening an existing one, jump to the module that matches your current pain.