Author Data Policies
Select classified data, assign supported protection permissions, and save a reviewable Data draft.
Use Policy to propose protection, review changes, and follow delivery. Saving, approving, and protecting data produce different results. A draft holds proposed changes. A governed revision records approved intent. Compilation generates configuration for Policy Integration Manager (PIM) or Federated Guardrails. Publication delivers that configuration. After approval, follow the delivery guide to check whether the receiving product retrieved or applied it. Refer to states and revisions before interpreting a policy’s status.
Start with access and preparation. Then follow the first-policy journey.
For other common tasks, use these guides:
Authors need edit capability and applicable policy access. Reviewers need review capability. Approvers need approval capability. These responsibilities do not define additional product roles. For an existing policy, ask its owner for owner/editor access in addition to the author role. Refer to roles and permissions.
For orientation, use the workflow map and use cases. For ongoing automation, see automatic recompilation. For failed delivery, follow recovery.
Select classified data, assign supported protection permissions, and save a reviewable Data draft.
Configure Federated Guardrails permissions, inspect preview, and save an artificial intelligence policy for governance.
Hand off saved policy work between authors, reviewers, and approvers without confusing approval with delivery.
Separate approval, publication, consumer receipt, and target-specific protection evidence.
Follow a Data policy from a saved draft through separate-user review and delivery checks.
Choose a canonical journey for authoring, review, delivery, or retirement.
Keep policy scope, review decisions, concurrency evidence, and target verification explicit.
Match reader responsibilities to policy authoring, inspection, governance, and recovery outcomes.
Find policies, inspect current content and history, and choose authorized lifecycle actions.
Choose the Data or artificial intelligence authoring lane and follow its canonical tasks.
Choose a task for editing, submitting, approving, restoring, or archiving a policy.
Understand how discovery, principal catalogs, native policy context, and target delivery affect policy work.
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