[FEA] it is hard to get the schema when you do several workflows

🚀 Feature request

It would be great if we can better keep track of the schema, cardinality and other features. There are a better way to deal with columns than with the schema?

Motivation

I am a bit frustrated when I try to feed the schema into Transformers4Rec. I am trying to adapt the competition code from Coveo Recsys competition to Transformers4Rec.

Being a more complex example than the ones that are updated to 0.7.x nvt and that uses t4r in the examples, I am a bit lost trying to feed/create the schema to use it in t4r.

Following the competition example, it uses several workflows and then it keeps doing changes in pandas, so keeping track of the schema is really hard. Would it be possible to get the dataset statistics (cardinality, max, min, categorical or continuous) automatically without the need of being extracting it from the workflows/nvt.dataset()? So we can keep doing changes to the dataset without the limitation of extracting the schema from there.

Maybe there are actually a proper way of getting the schema but I have been a bit lost.

Your contribution

I am open to discussion and thinking a way to automatically get the schema.

Start by reviewing the linked Coveo competition example and the workflow and nvt.dataset() references in the issue to understand how schema, cardinality, and column statistics are currently obtained. Clarify the desired behavior for datasets changed across multiple workflows and pandas steps; done should mean those statistics can be obtained automatically and consumed by Transformers4Rec.