Data governance built to hold up when AI starts asking questions.
Data governance is the prerequisite for AI.
Before a model, a dashboard, or an executive can trust an answer, the data behind it needs a single definition, a clear owner, and a rule that catches it when something breaks.
“How Snowflake Supports Data Governance” with Teresa Kovich, Principal Consultant | DAS42
WHY THIS MATTERS TODAY
Governance gets marketing, finance, and customer success working from the same definition of “active customer,” instead of multiple versions.
That consistency is what makes AI worth trusting: a model built on agreed-upon data gives answers people can act on.
HOW DAS42 DELIVERS
DAS42 builds data governance directly into your Snowflake environment rather than layering a separate governance tool on top of it. Two ways clients typically engage:
Scoped engagement.
A defined governance framework and quality-check build for a specific domain or data set, with a clear deliverable and timeline.
Embedded team.
DAS42 governance specialists work inside your existing data team on an ongoing basis, building and maintaining rules as your data model evolves.
SOLUTIONS USED FOR DATA GOVERNANCE
WHERE GOVERNANCE RUNS
Snowflake role-based access control and dynamic data masking
Snowflake object tagging and data lineage
MDM42, DAS42’s Snowflake-native master data management accelerator
dbt Labs, for teams with an existing dbt-based governance workflow
DAS42 allows us to offer our customers far greater visibility into their network while enabling us to achieve scalable, cost-effective business practices. They provide deep expertise, a unique approach, and agility in execution, resulting in real business value from BI analytics.
– Jon Moss, Vice President of Digital Transformation, Spectrotel