Data dreams die in silos
In most organizations, data exists in pockets across apps, public and private clouds, and on premises. And that’s a problem — most organizations tell us they don’t even know what data they have, never mind who has access, how it’s being used or if it’s any good.
This disconnect has created problem after problem, preventing many organizations from effectively using and governing their data.
While this feels like a lot of discrete problems, they’re actually symptoms of a larger issue: governance fragmentation. When your visibility, access and policies are fragmented across all your different clouds, apps and data stores, you can’t operationalize your governance strategies.
And it’s not just about technical silos. The disconnect extends to people, as most systems offer no way to bring business users into the process of governing, stewarding and accessing data.
See how overcoming governance fragmentation lets you move faster on every data and AI use case
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Why technical data catalogs alone don’t solve governance fragmentation
Lots of vendors promise to unify governance — which sounds like it would solve the problem of fragmentation — but there tend to be big limitations for complex organizations.
For instance, governance that’s tethered to compute systems means you only govern the data in that compute system. And moving everything to a public cloud will limit you; what about your app data stored in the app makers’ clouds, or things you need to move onsite for security reasons? (Not to mention, cloud lock-in).
And technical data catalogs have limitations, too: most don’t talk to each other, and they also leave nontechnical stakeholders in the dark.
True unified governance — the kind that solves governance fragmentation — needs these capabilities:
Tie together visibility and control for every place data lives
Work across any data engine, compute system, tool or AI use case
Allow centrally managed policies while providing flexibility for federated governance
Build on a unified platform with common metadata and AI to allow automation of data stewardship tasks as they scale
Uses automation to discover sensitive data to improve compliance
Measure and inform you of the quality levels of your data
Track (and show) lineage as data flows, transforms and gets used
Support every user type
