In my quest to bring myself up to date with where the data & analytics engineering world is at nowadays, I’m going to build on my exploration of the storage and access technologies and look at the tools we use for loading and transforming data.

I started my dbt journey by poking and pulling at the pre-built jaffle_shop demo running with DuckDB as its data store. Now I want to see if I can put it to use myself to wrangle the session feedback data that came in from Current 2022. I’ve analysed this already, but it struck me that a particular part of it would benefit from some tidying up - and be a good excuse to see what it’s like using dbt to do so.

I’ve been wanting to try out dbt for some time now, and a recent long-haul flight seemed like the obvious opportunity to do so. Except many of the tutorials with dbt that I found were based on using Cloud, and airplane WiFi is generally sucky or non-existant. Then I found the DuckDB-based demo of dbt, which seemed to fit the bill (🦆 geddit?!) perfectly, since DuckDB runs locally. In addition, DuckDB had appeared on my radar recently and I was keen to check it out.

This is one of those you had to be there moments. If you come into the world of data and analytics engineering today, ELT is just what it is and is pretty much universally understood. But if you’ve been around for …waves hands… longer than that, you might be confused by what people are calling ELT and ETL. Well, I was ✋.