Data silos are the natural result of decentralized systems and tooling decisions that optimize for individual departments rather than the organization as a whole. Common entities like "client," "customer," or "user ID" often differ across departments, complicating data integration -- custom ETL (extract, transform, load) processes (read: spaghetti code) that are challenging to scale and maintain. It doesn't have to be that way.
In the world of enterprise data management, text-to-SQL technology, while helpful, is it simply not enough for today’s complex data environments?
Uncover the risks of openwashing in AI tools like ChatGPT. Learn about the Linux Foundation's new tools for ensuring model transparency and protecting your interests.
