Data Foundation & Governance
Trust, trace, and defend every number in the warehouse.
Catalog, column-level lineage, anomaly-detecting observability, access control, and data contracts, so you can see who can access what, trace where a number came from, and know the moment a pipeline breaks.
We have a warehouse, but who can see what, where did this number come from, and how do we know when it breaks?
A platform without governance is a liability in a regulated industry: access is unclear, lineage is a mystery, and a broken pipeline is discovered by the executive whose dashboard went wrong. This project makes the platform governed and observable, so data is traceable, access is controlled and auditable, and breakages surface automatically before they reach a decision.
What's included
Catalog and lineage
A data catalog with column-level lineage, captured automatically and surfaced in context for impact analysis.
Observability and anomaly detection
Observability across the five pillars (freshness, volume, distribution, schema, lineage) with ML-based anomaly detection that auto-baselines.
Access and compliance
Access and compliance controls: role and attribute-based access, least privilege, masking, and audit logging, HIPAA and PHI-aware.
Data contracts
Schema and SLA contracts enforced in CI, so a producer's change can't silently break downstream consumers.
How it works
- 1
Catalog and trace
We stand up the catalog and automated column-level lineage for impact analysis and provenance.
- 2
Observe
We add observability and anomaly detection across the five pillars so breakages surface on their own.
- 3
Govern and contract
We put access, compliance controls, and CI-enforced data contracts in place.
What you walk away with
- A catalog with automated, column-level lineage
- Observability across five pillars with ML anomaly detection
- HIPAA-aware access control, masking, and audit logging
- Data contracts enforced in CI so changes can't silently break consumers
Frequently asked
- What needs to be in place first?
- A data platform to govern, from Data Platform Install or an equivalent. Governance and observability are layered onto a working warehouse.
- Why does life sciences need this specifically?
- Regulated data demands provenance, controlled and audited access, and the ability to prove where a number came from. Lineage, masking, and audit logging make the platform defensible, not just functional.
Make the platform defensible
Book a consultation to govern and observe your data, so you can trust, trace, and defend every number.
Where this leads next
Single Customer View
Resolve identity into a Customer 360 on the governed foundation.
Explore the package