Member-only story
How I Organize My Snowflake Data Warehouse
The databases, schemas, and tables where you should store your data
Your data warehouse is the hub of your modern data stack. Data flows into it through data ingestion tools like Airbyte, making sure raw data is available. Data is transformed within it using SQL and modern data transformation tools like dbt. Data then flows out of it to business users and data visualization platforms.
All data exists within your warehousing solution.
It’s a powerful tool. And one that you need to make sure you do right. The integrity of your data depends on the analytics engineers, data engineers, and data analysts that set this solution. It is imperative that it is done correctly, considering different factors like development and production, security, and business use cases.
In this article, I explain how I organize my Snowflake data warehouse so that as little as possible goes wrong. I cover deciding on your data warehouse solution, determining your databases, schemas and different types of tables.
Why choose Snowflake as your data warehouse?
I’ll be specifically referencing Snowflake as my data warehouse solution throughout this article. Snowflake is what I believe to be the best data…
