Purpose
Explain why the policy exists and what risk it controls.
4.8
on G2
Free Data, AI & Analytics Template
Policy for classifying, accessing, and retaining [data domain]
Use this template to policy for classifying, accessing, and retaining [data domain].
| Field | Details |
|---|---|
| Category | Data, AI & Analytics |
| Owner | [Team or owner] |
| Version | [Version number] |
| Effective Date | [Date] |
| Review Cycle | [Monthly / Quarterly / Annual / Event-based] |
| Status | [Draft / In Review / Approved] |
Explain why the policy exists and what risk it controls.
| Item | Details | Owner | Status |
|---|---|---|---|
| [Item or requirement] | [Describe the relevant detail, evidence, or decision] | [Owner] | [Open / Complete] |
| [Item or requirement] | [Describe the relevant detail, evidence, or decision] | [Owner] | [Open / Complete] |
[Add context, assumptions, exceptions, evidence links, screenshots, calculations, or reviewer comments.]
Define covered datasets, systems, teams, and exclusions.
| Item | Details | Owner | Status |
|---|---|---|---|
| [Item or requirement] | [Describe the relevant detail, evidence, or decision] | [Owner] | [Open / Complete] |
| [Item or requirement] | [Describe the relevant detail, evidence, or decision] | [Owner] | [Open / Complete] |
[Add context, assumptions, exceptions, evidence links, screenshots, calculations, or reviewer comments.]
List sensitivity levels, examples, labels, and handling requirements.
| Item | Details | Owner | Status |
|---|---|---|---|
| [Item or requirement] | [Describe the relevant detail, evidence, or decision] | [Owner] | [Open / Complete] |
| [Item or requirement] | [Describe the relevant detail, evidence, or decision] | [Owner] | [Open / Complete] |
[Add context, assumptions, exceptions, evidence links, screenshots, calculations, or reviewer comments.]
Describe approval workflow, least privilege, audit logging, and periodic review.
| Item | Details | Owner | Status |
|---|---|---|---|
| [Item or requirement] | [Describe the relevant detail, evidence, or decision] | [Owner] | [Open / Complete] |
| [Item or requirement] | [Describe the relevant detail, evidence, or decision] | [Owner] | [Open / Complete] |
[Add context, assumptions, exceptions, evidence links, screenshots, calculations, or reviewer comments.]
Define retention periods, archival rules, deletion triggers, and legal holds.
| Item | Details | Owner | Status |
|---|---|---|---|
| [Item or requirement] | [Describe the relevant detail, evidence, or decision] | [Owner] | [Open / Complete] |
| [Item or requirement] | [Describe the relevant detail, evidence, or decision] | [Owner] | [Open / Complete] |
[Add context, assumptions, exceptions, evidence links, screenshots, calculations, or reviewer comments.]
Require source ownership, transformation documentation, and downstream dependency tracking.
| Item | Details | Owner | Status |
|---|---|---|---|
| [Item or requirement] | [Describe the relevant detail, evidence, or decision] | [Owner] | [Open / Complete] |
| [Item or requirement] | [Describe the relevant detail, evidence, or decision] | [Owner] | [Open / Complete] |
[Add context, assumptions, exceptions, evidence links, screenshots, calculations, or reviewer comments.]
Document review cadence, evidence, exceptions, and accountable approvers. Use clear policy language and Markdown tables.
| Item | Details | Owner | Status |
|---|---|---|---|
| [Item or requirement] | [Describe the relevant detail, evidence, or decision] | [Owner] | [Open / Complete] |
| [Item or requirement] | [Describe the relevant detail, evidence, or decision] | [Owner] | [Open / Complete] |
[Add context, assumptions, exceptions, evidence links, screenshots, calculations, or reviewer comments.]
Template Structure
Use this data, ai & analytics template as a starting point, then customize each section to match your internal workflow, evidence, and signoff needs.
Explain why the policy exists and what risk it controls.
Define covered datasets, systems, teams, and exclusions.
List sensitivity levels, examples, labels, and handling requirements.
Describe approval workflow, least privilege, audit logging, and periodic review.
Define retention periods, archival rules, deletion triggers, and legal holds.
Require source ownership, transformation documentation, and downstream dependency tracking.
Document review cadence, evidence, exceptions, and accountable approvers. Use clear policy language and Markdown tables.
Write a Data Governance Policy. Structure with:
Explain why the policy exists and what risk it controls.
Define covered datasets, systems, teams, and exclusions.
List sensitivity levels, examples, labels, and handling requirements.
Describe approval workflow, least privilege, audit logging, and periodic review.
Define retention periods, archival rules, deletion triggers, and legal holds.
Require source ownership, transformation documentation, and downstream dependency tracking.
Document review cadence, evidence, exceptions, and accountable approvers.
Use clear policy language and Markdown tables.
Covers customer profile, product usage, billing status, and support interaction datasets used for analytics.
| Class | Examples | Handling |
|---|---|---|
| Internal | Aggregated feature usage | Team access permitted |
| Confidential | Account ARR, contract tier | Approved analytics roles only |
| Restricted | Email, phone, billing address | Mask by default |
Access requires manager approval, data owner approval, and quarterly recertification.
Raw customer event logs are retained for 18 months, then aggregated or deleted unless under legal hold.
Record a walkthrough, training session, or process demonstration. Docsie AI turns it into structured documentation using this template as the starting framework.
Use the template manually, or let Docsie generate the first draft from source footage.
Plan, metrics, and decision rules for [experiment]
Definition and acceptance criteria for a [dashboard] build
Release notes for [dashboard], metric, model, or dataset changes
Field-level reference for [dataset], table, or reporting model
Reusable checks for validating [dataset] before release
Operational runbook for [ETL pipeline] failures and reruns
Template FAQ
Common questions about using and generating a data Governance Policy.
Q: What is a data Governance Policy?
A: A data Governance Policy is a structured document for policy for classifying, accessing, and retaining [data domain].
Q: Can I download this data Governance Policy as Word or PDF?
A: Yes. This page includes free downloads in DOCX, PDF, and Markdown formats so you can edit, share, or import the template into your documentation system.
Q: Can Docsie generate this from a video?
A: Yes. Upload a process walkthrough, training recording, or screen capture to Docsie, then use this template structure to generate a first draft automatically.