Document
Data Governance
Data Governance
Compliance
Data Quality
Data Governance Policy Template
••Olivier Soudée
Customizable data governance policy template for roles, access, and compliance. Covers 5 core policy areas and review cadence.
Template Overview
This template provides a structured framework for creating data governance policies. It includes all essential sections with guidance on what to include and how to customize for your organization's needs.
Use this template as a starting point and adapt the content to reflect your specific:
- Organizational structure
- Regulatory requirements
- Industry standards
- Data landscape
How to Use This Template
- Copy the template to your preferred document format
- Replace bracketed text with your organization's specifics
- Review with stakeholders including legal, compliance, IT, and business
- Obtain approval from your data governance council
- Publish and communicate to all relevant employees
- Schedule regular reviews (recommended: annually)
Template Content
[Organization Name] Data Governance Policy
Version: [X.X] Effective Date: [Date] Last Reviewed: [Date] Policy Owner: [Role/Name] Approved By: [Data Governance Council / Executive]
1. Purpose
This policy establishes the framework for governing data across [Organization Name]. It defines roles, responsibilities, and standards to ensure data is managed as a strategic asset while maintaining quality, security, and compliance.
1.1 Objectives
This policy aims to:
- Establish clear accountability for data assets
- Ensure data quality meets business requirements
- Protect sensitive data from unauthorized access
- Enable compliant use of data across the organization
- Support data-driven decision making
2. Scope
2.1 Data Coverage
This policy applies to:
- All data created, collected, processed, or stored by [Organization Name]
- Data in all formats: structured, unstructured, and semi-structured
- Data in all locations: on-premises, cloud, third-party systems
2.2 Organizational Coverage
This policy applies to:
- All employees of [Organization Name]
- Contractors and consultants with data access
- Third-party vendors processing our data
- [Add other applicable groups]
2.3 Exclusions
This policy does not cover:
- [List any explicit exclusions]
3. Definitions
| Term | Definition |
|---|---|
| Data Asset | Any collection of data that has value to the organization |
| Data Domain | A logical grouping of related data (e.g., Customer, Product, Financial) |
| Data Owner | Business executive accountable for a data domain |
| Data Steward | Individual responsible for day-to-day data management |
| Data Custodian | Technical role responsible for data storage and security |
| Metadata | Data that describes other data (definitions, lineage, quality rules) |
| PII | Personally Identifiable Information |
| [Add organization-specific terms] | [Definitions] |
4. Governance Structure
4.1 Data Governance Council
Purpose: Provide strategic oversight for data governance initiatives.
Composition:
- Chief Data Officer (Chair)
- [List other members/roles]
Responsibilities:
- Set data governance strategy and priorities
- Approve data policies and standards
- Resolve cross-domain data issues
- Allocate resources for data initiatives
Meeting Cadence: [Monthly/Quarterly]
4.2 Data Owners
Responsibilities:
- Define business requirements for data in their domain
- Approve data access requests
- Ensure compliance with data policies
- Assign data stewards
- Escalate unresolved issues to the governance council
4.3 Data Stewards
Responsibilities:
- Maintain data quality within their domain
- Document business metadata and data definitions
- Implement data governance policies
- Provide training and support to data users
- Report on data quality metrics
4.4 Data Custodians
Responsibilities:
- Implement technical security controls
- Manage data storage and backup
- Execute data retention and archival procedures
- Support data access provisioning
- Maintain technical metadata
5. Data Classification
All data assets must be classified according to the following scheme:
5.1 Classification Levels
| Level | Description | Examples | Handling Requirements |
|---|---|---|---|
| Public | No restrictions on disclosure | Marketing materials, public website | Standard controls |
| Internal | For internal use only | Internal reports, org charts | Access logging |
| Confidential | Sensitive business information | Financial data, strategies | Encryption, need-to-know access |
| Restricted | Highest sensitivity | PII, PHI, trade secrets | Encryption, MFA, audit trail |
5.2 Classification Responsibilities
- Data Owners are responsible for classifying data in their domain
- Default classification for unclassified data is [Internal/Confidential]
- Classification must be reviewed [annually/upon significant change]
6. Data Quality
6.1 Quality Dimensions
Data quality will be measured across these dimensions:
- Accuracy: Data correctly represents real-world values
- Completeness: All required data is present
- Consistency: Data values are uniform across systems
- Timeliness: Data is current and updated as required
- Validity: Data conforms to defined formats and rules
- Uniqueness: No unintended duplicate records
6.2 Quality Standards
| Data Domain | Accuracy | Completeness | Timeliness |
|---|---|---|---|
| Customer | ≥99% | ≥98% | ≤24 hours |
| Product | ≥99.5% | ≥99% | ≤4 hours |
| Financial | ≥99.9% | ≥99.9% | ≤1 hour |
| [Domain] | [Target] | [Target] | [Target] |
6.3 Quality Monitoring
- Data quality will be monitored [continuously/daily/weekly]
- Quality scores will be reported to the Data Governance Council
- Issues below threshold require remediation plans within [X] days
7. Data Security
7.1 Access Control
- Access to data is granted on a need-to-know basis
- All access requests require Data Owner approval
- Access must be reviewed [quarterly/annually]
- Access is revoked upon role change or termination
7.2 Data Protection
- Confidential and Restricted data must be encrypted at rest and in transit
- Multi-factor authentication required for Restricted data access
- Data masking required for non-production environments
8. Compliance
This policy supports compliance with:
- [GDPR / CCPA / HIPAA / SOC 2 / etc.]
- [Industry-specific regulations]
- [Internal policies]
Non-compliance may result in disciplinary action.
9. Policy Maintenance
9.1 Review Schedule
This policy will be reviewed:
- Annually by the Data Governance Council
- Upon significant regulatory changes
- Upon major organizational changes
9.2 Exception Process
Exceptions to this policy require:
- Written request to Data Governance Council
- Risk assessment documentation
- Compensating controls identification
- Time-limited approval
10. Contact
For questions about this policy, contact:
Data Governance Office Email: [data-governance@organization.com] [Additional contact information]
Revision History
| Version | Date | Author | Changes |
|---|---|---|---|
| 1.0 | [Date] | [Name] | Initial release |
Customization Tips
- Tailor classifications: Adjust the data classification scheme to match your industry requirements
- Set realistic targets: Data quality targets should be achievable and measurable
- Include regulatory specifics: Add sections for GDPR, HIPAA, or other regulations as needed
- Add appendices: Include reference materials, forms, and detailed procedures
- Version control: Maintain clear version history and approval records
Related Resources
- Explore more guides - Browse governance implementation guides
- Data Strategy Assessment Checklist - Assess maturity before implementing governance
- What is Data Strategy and Why Does Your Organization Need One? - Governance supports overall data strategy
- Building a Data Governance Framework - Complete implementation guide for establishing governance
- How to Measure Data Quality - Practical approaches to defining quality metrics for your policies
Sources & references
- GDPR (Regulation EU 2016/679)— European Union
- AI Act (Regulation EU 2024/1689)— European Union