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sdw-online/postgres-dwh: A Postgres data warehouse for processing synthetic data using IAC principles

github.com · 1,608 words · saved by 1 readers

Disclaimer: This was just for fun. In a real-world setting there are more appropriate options that address modern-day warehousing challenges for different businesses depending on the problem statement at hand, so consider your company's (or client's) unique challenges before replicating any techniques used in this blog. This is a quick-fire project to demonstrate an event-driven Postgres data warehouse can be built using vanilla Python and SQL code while remaining performant and highly available for analytical use cases. Here's why I used each language: Python - for creating the pipelines connecting the different layers SQL - for creating and querying the Postgres tables Although cloud data warehouses are growing increasingly popular in the analytics world, there are still scenarios where traditional data warehouses would serve an enterprise better than a cloud data warehouse. More on this will be shared in a future blog post. I create a GitHub repo called postgres-dwh and set up the r

Preface Disclaimer: This was just for fun. In a real-world setting there are more appropriate options that address modern-day warehousing challenges for different businesses depending on the problem statement at hand, so consider your company's (or client's) unique challenges before replicating any techniques used in this blog. Why build this...? This is a quick-fire project to demonstrate an event-driven Postgres data warehouse can be built using vanilla Python and SQL code while remaining performant and highly available for analytical use cases. Here's why I used each language: Python - for

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