Comparing {targets} in R to dbt for Data Engineering

Jonathan Carroll compares two approaches:

Thinking of a real-world project I could take for a spin, I decided to build some ingestion for my personal finances. I’ve used Quickbooks previously which connects up to my bank and helps categorise personal and business (as a freelance contractor) expenses. I decided I’ll build my own ‘slowbooks’ processing workflow based on some manual exports (I don’t think my bank has an API).

Both of the approaches I’ll compare here build on the idea of a Makefile which connects up commands to run based on dependencies, and only runs what is needed; if all the input dependencies of a step have not changed, there’s no need to re-run that step. From what I understand, you could largely get away with just writing some Makefiles (or the newer implementation just (just.systems)) but these two approaches help to better structure how that’s constructed.

Read on for Jonathan’s discovery process and ultimate findings. H/T R-Bloggers.