What the program covers
Program Overview
- Week 1: How databases store information
- Tables, rows, columns, primary keys. Relational vs document-based storage. When each makes sense.
- Week 2: Relationships between data
- One-to-many, many-to-many. Foreign keys. How joins work conceptually.
- Week 3: Reading and writing data
- Basic SELECT queries. Filtering and sorting. What happens when you update or delete records.
- Week 4: Performance and scale
- Indexes, query speed, caching basics. Why some features are slow and what engineers do about it.
- Week 5: Database decisions in product context
- Schema changes, migrations, technical debt. How to evaluate engineering estimates related to data work.
About this course
A lot of product decisions get constrained by database structure that was set up years ago. Changing it is expensive and slow. Understanding why helps you make better decisions earlier, before the architecture locks you in.
What this is not
This is not an SQL course. You will write a few simple queries to understand what is happening, but the focus is conceptual: how data is organized, why it matters, and what questions to ask your engineering team.
Topics that come up in real product work
Why adding a feature sometimes requires a database migration. What normalization means and when it causes problems. How indexing affects query speed and why that matters for user experience. These are not abstract concepts here.
Who finds this most useful
Product managers who have been told a feature is too complex without understanding why. Analysts who write reports but do not control the data structure they work with. Operations leads managing tools built on databases they cannot read.
I finally understood why our reporting was so slow. It was not a bug, it was how the tables were structured from day one.
Format
Five weeks, one live session per week plus async materials. Each session is 90 minutes with time for questions.