Better Data Models (redux)
Lately there have been quite a few posts and articles about what is needed for AI to be successful. In the data world, that means high quality data is table stakes. But it’s not just the data in your database. It’s having nailed down the semantic meaning of that data (in business terms) and all the context surrounding that data (including relationships to other data and systems).
It sounds like we need to get back to the basics of good #datamanagment (like #DAMA has taught for decades via their DMBOK and certifications).
And that gets back to having a well curated #datamodel (you must have seen that coming from me!). And that then reminded me that I once wrote a book with a Checklist for Data Model Design Reviews. And it is still available on Amazon! Check it out: https://lnkd.in/gVE4u5FR
By no means is it everything you need to be successful in building a data driven #AI agent or process, but if you have not looked at your data models in years, or (more likely) don’t have one, this will get you started in the right direction to at least ask the questions of your data team to see where you are.
The output from AI is only as good as the information we make available to it. So get going and make sure your data is indeed #AIReady.
NB – the book mentions specific data modeling tools I have used in the past, but the concepts and questions can be applied to any modeling tool you are using today.
Model on!
Kent G
The Data Warrior 