My bias has always been against click-and-drag programming, and I believe it mostly comes from my application developer background as the sentiment towards visual style application development tools is (almost) unanimously negative.
Coming over to the data world, I noticed the same type of problems click-and-drag app development had appearing in tools like IBM's DataStage and Informatica's Powercenter. There's only so much you can do by dragging and dropping items on a screen, eventually you need to take their respective escape hatches and do some programming - and when you do it's almost never ideal. I've also yet to see a visual coding tool produce readable concise diffs in any source control provider. Most of these tools also require some sort of centralized server infrastructure and a thick client making it so much more challenging to bootstrap new ETL developers.
I do hear others in the data world who have migrated to Spark or DBT share the same sentiments - but that could just be confirmation bias.
Coming over to the data world, I noticed the same type of problems click-and-drag app development had appearing in tools like IBM's DataStage and Informatica's Powercenter. There's only so much you can do by dragging and dropping items on a screen, eventually you need to take their respective escape hatches and do some programming - and when you do it's almost never ideal. I've also yet to see a visual coding tool produce readable concise diffs in any source control provider. Most of these tools also require some sort of centralized server infrastructure and a thick client making it so much more challenging to bootstrap new ETL developers.
I do hear others in the data world who have migrated to Spark or DBT share the same sentiments - but that could just be confirmation bias.