As a solo senior dev working on a data warehouse, I’ve found myself wondering what features to include in my YAML config file. With no colleagues to bounce ideas off of, I turned to the community for help.
Currently, my YAML file includes table definitions, column and table descriptions, loading types, and essential configurations like connection and target setup. But I wanted to know: what else should I be including?
Essential Configurations
- Table definitions: A must-have for any data warehouse. Define your tables, and you’re off to a great start.
- Column and table descriptions: Clear descriptions make it easier to understand your data and make informed decisions.
- Loading types: Specify how your data loads, and you’ll avoid headaches down the line.
- Connection and target configs: The foundation of your data warehouse. Get these right, and you’re golden.
Taking it to the Next Level
So, what else can you include in your YAML file? Here are some ideas:
- Data quality checks: Ensure your data meets certain standards before loading it into your warehouse.
- Data transformation rules: Define how to transform your data for better analysis and insights.
- Security and access controls: Protect your data with fine-grained access controls and encryption.
- Monitoring and logging: Keep an eye on your data warehouse’s performance and identify issues before they become major problems.
As a Python and SQL stack enthusiast, I’m curious to hear from others who share my passion. What features do you find most useful in your YAML files or data engineering suite?
Share your experiences and tips in the comments below! And if you’re stuck with MSSQL like me, let’s commiserate and find ways to make the most of it.
*Further reading: YAML Configuration Files*