Data governance best practices: what IAM teams should change

TL;DR: Data governance best practices now depend on identity controls as much as policy design, because compliance, access oversight, and auditability all fail when data ownership and entitlements are not aligned, according to Netwrix. The practical shift is that data governance programmes must be run as an access governance problem across human, non-human, and autonomous identities, not as a documentation exercise.

NHIMG editorial — based on content published by Netwrix: 10 data governance best practices for compliance

Questions worth separating out

Q: How should organisations align data governance with identity governance?

A: Organisations should align them by treating every data policy as an access control problem.

Q: Why do non-human identities complicate data governance?

A: Non-human identities complicate data governance because they access data at machine speed, often outside human review loops.

Q: How can teams tell whether data classification is actually working?

A: Teams can tell classification is working when labels change real access decisions, logging, and review outcomes.

Practitioner guidance

• Tie data owners to entitlement owners Require every sensitive dataset to have an accountable owner for the access paths that reach it, including application roles and non-human credentials.
• Inventory non-human access to governed data Build a current inventory of service accounts, API keys, tokens, and certificates that can read, write, or export governed datasets.
• Make classification enforceable at the access layer Check that sensitive-data labels trigger real controls such as conditional access, logging, and least-privilege scope on both human and machine identities.

What's in the full article

Netwrix's full blog covers the operational detail this post intentionally leaves for the source:

• Practical governance checklists for ownership, classification, and accountability that can be applied during programme rollout.
• Implementation detail on how to connect data controls to access review and audit workflows.
• Operational guidance for reducing risk around sensitive data, retention, and access visibility.
• Examples of governance tasks that matter when teams are preparing for compliance reviews.

👉 Read Netwrix's 10 data governance best practices for compliance →

Data governance best practices: what IAM teams should change?

Explore further

View Full Forum →  |  NHI Foundation Course →