What Dawiso is
Dawiso is governance for the data that AI depends on. It combines a data catalog, a business glossary and lineage tracking with an AI context layer, so teams can see what data means, where it came from and what is allowed to use it.
What you can do with it
- Catalogue data assets across systems
- Maintain agreed definitions in a glossary
- Trace lineage for reports and models
- Give AI features a governed context
- Control who can access what
Who it is for
- Data governance teams
- Enterprise architecture groups
- Data platform teams adopting AI
What to watch out for
- A catalog is only as current as its metadata automation; stale entries mislead more than none
- Catalogs may include personal or confidential fields, so the catalog itself needs access control
- Adoption depends on people maintaining definitions, which is organisational work
- Confirm how lineage is derived and what happens when a source changes
Pros & cons
✓ What we like
- Clarity on what data actually means
- Lineage supports audit and trust
- Context layer helps AI adoption
! What to watch out for
- Metadata must be kept current
- Catalog itself is sensitive
- Adoption is organisational work
FAQ
What does it combine?
A data catalog, glossary, lineage tracking and an AI context layer.
Who benefits?
Data governance teams, enterprise architects and data platform teams.
What should I check?
How current metadata is and who can see catalog entries.
Last reviewed: 2026-09-18
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