When an AI project does not deliver the expected results, the cause usually lies in the data: incomplete, duplicated, outdated or without a clear owner.
The pillars of data governance
- Defined roles and responsibilities.
- An accessible data catalogue.
- Measurable quality rules.
- Access and privacy policies.
Why start with data
Investing in these pillars first speeds up any subsequent analytics or artificial intelligence initiative.
If you want to establish or review your organisation's data governance , we can tell you how we approach it at CGC.
