Big organizations love to fret about data silos - teams or groups that have their own databases, data warehouses, data lakes, (lake houses?) etc. separate from the rest of the org. They invest huge amounts of time and energy into creating technical solutions that will allow all these teams to share their data and coordinate their operations.
The problem is that often, the blocker isn’t the system or the software. It’s how the teams conceptualize and interact with the data. If teams use different definitions of concepts like revenue or experiment or project, how are you going to pick which definition will be used as the source of truth? If teams don’t have functioning communication channels and a shared understanding, what will stop them from building schematic silos inside a shared database?
When you encounter a technical-looking problem like data silos, it’s tempting to address it with a technical solution. That’s what we’re trained for, and that’s usually the more interesting, and often easier-sounding, approach. But any technical solution will be doomed to failure until you address the underlying organizational issue. As promising as a technical solution may be, organization will beat technology every single time.