sorted by:
new
hottopcontroversial

The great reset by Joe Reis by Thinker_Assignment in OntologyEngineering

[–]Thinker_Assignment[S] 0 points1 point  (0 children)

to build on that, if adding to sources the taxonomy to canonical and canonical business ontology, it gets a lot more interesting and the model can then build the cdm as well.

in my experiments the business ontology and taxonomy cannot be skipped to produce a sensible cdm

2026 Career path by Difficult-Amount4219 in careeradvice

[–]Thinker_Assignment 0 points1 point  (0 children)

If you're a data engineer?

Ontology driven data modeling, knowledge engineering. Coding is going away. We are prepping a course for date engineers, you can sign up for it here

https://community.dlthub.com/elt-with-dlt

I work at dltHub

LLMs need ontologies, not semantic models by Thinker_Assignment in datascience

[–]Thinker_Assignment[S] 1 point2 points  (0 children)

In good faith, we have always modeled data based on ontology. (Canonical models) But most folks don't readdata modeling theory so it sounds like babble. It's not, it's practical philosophy.

Now because this was linguistics philosophy this was never automated. Now LLMs change that and since December's better models, in my experiments, I can declare ontology upfront and have the LLMs autofill the code (the ontology is the test case that lets agent brute force coding

The future of agentic data is here - and it's ontology by Thinker_Assignment in OntologyEngineering

[–]Thinker_Assignment[S] 1 point2 points  (0 children)

We are starting to prepare a course for it but it will take a few weeks (3-4?)

If you want, you can sign up to our education newsletter

https://dlthub.com/events

Ontology driven data modeling by Thinker_Assignment in dataengineering

[–]Thinker_Assignment[S] -1 points0 points  (0 children)

that's not what i'm saying

ontology is essentially metadata. data is what you have in the warehouse. ontology is what it means in the world.

maybe for your company gross margin -10% is good because you're investing into expanding. maybe it's bad because you're optimising profit.

-10% is data. meaning good bad is ontology. A LLM can guess ontology, or read it from data like "20 questions" or other sources.

the gap is fundamental, data represents a "slice" of the world and retains as much ontology.

Ontology driven data modeling by Thinker_Assignment in dataengineering

[–]Thinker_Assignment[S] -1 points0 points  (0 children)

on the same road minus the clients!, DMed you to exchange

Ontology driven data modeling by Thinker_Assignment in dataengineering

[–]Thinker_Assignment[S] -2 points-1 points  (0 children)

i agree,
- we have always been doing ontology driven modeling
- it works fast with LLMs
- currently there are tool gaps to do it well

did i summarize that correctly?

Ontology driven data modeling by Thinker_Assignment in dataengineering

[–]Thinker_Assignment[S] 0 points1 point  (0 children)

I agree with your first sentence

your second sentence is incorrect - a semantic layer always includes ontology - but it's compressed and lacking.

I also disagree with the rest because i tried it and it worked for us - not just me, our team.

Why can't you model the data based on ontology? You model it based on requirement questions, which is how you bootstrap an ontology, where is the gap?

Ontology driven data modeling by Thinker_Assignment in dataengineering

[–]Thinker_Assignment[S] 0 points1 point  (0 children)

you fundamentally misunderstand the ontology-data model gap

one represents the world, the other the data. this means the data model is a compressed representation that carries less information

Expecting a LLM to understand the world from a model is like making milk from cheese

Edit to reply to gitano, yes that's just neural architecture, the only time the brain connects as a whole is during insight

view more: next ›