What is your estimate of the tine required to begin building on the new(old) foundation, discover all the problems after a large investment of effort, and then declare to all that ita the wrong path?

My personal pain is Tableau trying to move uo the stack into data orchestration and compute. Code is completely inaccessible.

Don’t build ETL on Tableau. They haven’t made meaningful product progress in 10 years and completely missed the changes in data transformation. They are playing catch-up, they don’t understand where the world is moving.

Tableau, once full of creatives, has been gutted by Salesforce since the acquisition.

> My personal pain is Tableau trying to move uo the stack into data orchestration and compute. Code is completely inaccessible.

Not really a Tableau user, but I bet they are doing it to increase vendor lock-in. Which has always been an industry wide problem, proliferation of APIs and languages for that reason. I am not even sure how this could be any different, if the remuneration in a capitalist society depends on scarcity of the traded product or service (and the commons are privatized as a means to increase it). Here, the commons are the common understanding, standard APIs, and interoperability.

But that’s the point - it’s just a promise. I have a similar career as the top comment, and turns out that Low code approaches only work when people who understand code use them. Be that Python or sql, real use cases are not the toy examples shown in all typical introductions to these tools.

That said, if this thing is customizable enough, a good data engineer can prepare canned steps that fit the general structure of the customer data process and it may have its place.

I imagine the use-case for low-code tools is when your ratio of "business experts" heavily outweighs programmers, and the cost of inefficient dev processes/tech debt is less than the cost of waiting to onboard people with a coding background.