A single record change can cascade through to affect a VP's numbers. Databricks ontologies let you formalize metrics as SQL views and answer executive queries consistently. But ontologies won't replace engineers, just help them scale.
Now, if you think about all those Lego blocks, all those potential changes to one record that can affect the number the VP gets, that's highly complex, right? And so it's kind of interesting to see whether the GenAI tools will be able to deal with that complexity better than us.
I sat through a demo yesterday of metric views and Omnigent, or not Omnigent, of ontology, Databricks ontology. And And just layering the 2 together. And to your point of things being just SQL, right? Like they're the metric views. If you could do the calculation in SQL, then you could create that metric for it, which will be— Which having enough context to put into your ontology layer and for it to be groomed in a way that When that COO or CDO or— it's a plain text question that they're going to get a correct, consistent answer for what they're asking. That all plays a role, right? Having those different layers within your system, that's going to be huge in the future, but none of that replaces data engineering.
Watch now | Recording of AURA - Anna Bergevin & Shane Gibson 21st September 2026
Watch now | Recording of AURA - Chris Gambill & Shane Gibson on 11th September 2026
