Nice article OP. I and a great many others suffer from the same struggles of bringing personal projects to “completion”, and I’ve gotta respect the resilience in the length of time you hung in there. However, not to be overly pedantic, but I always felt “data science” was an exploratory exercise to discover insights into a given data set. I always personally filed the efforts to create the pipeline and associated automation (i.e. identify, capture, and store a given data set - more commonly referred to as “ETL”) as a “data engineering” task, which these days is considered a different specialty. Perhaps if you scope your problem a little smaller, you may yet be able to capture something demonstrably valuable to others (and something you might consider “finished”). You’d be surprised how simple something that addresses a real issue can be to be able to provide real value for others.

Nice work and great effort.