What This Is
These are lessons I’ve learned solving real problems at QVC. They’re written from my experience — mostly Python, dbt, and DuckDB — but the underlying principles often transfer to other tools.
If you use R, Excel, or something else entirely, the concepts might still help even if the code doesn’t.
The Guides
| Guide | Problem It Solves |
|---|---|
| Automating Tableau Extracts | How to publish data to Tableau Server without opening Tableau Desktop |
| Building a Transformation Layer | How to structure transformations so you’re not starting from scratch every time |
| Working with Large Data Locally | How to handle datasets that push against your laptop’s RAM limits |
More guides coming as I document what I’ve learned.
How These Are Structured
Each guide follows a simple format:
- The Problem — What you’re trying to solve
- Why It Matters — Why the obvious approach doesn’t work
- The Solution — What I did
- The Code — Examples you can adapt
- Related — Links to deeper context in the Stack or Journey
A Note on Tool Choices
I use Python, dbt, and DuckDB because they solved my specific constraints (no cloud access, 16GB laptop, read-only Oracle). Your constraints might be different.
Where possible, I’ll note alternatives:
- If you’re using R, DuckDB has an R package
- If you’re using Excel/Power Query, some patterns translate
- If you have cloud access, you probably have better options than I did
The goal is to share what worked, not to prescribe what you should use.