What Is Data Governance?
Data governance is the overall management of data availability, usability, integrity, and security in an organization. It establishes who can take what actions, on what data, under what circumstances, using what methods.
Good data governance answers:
- Who owns this data?
- Who can access it?
- How should it be used?
- What quality standards apply?
- How long should it be retained?
- How is it protected?
Why Data Governance Matters
Without Governance
- Multiple conflicting definitions of “revenue”
- Sensitive data exposed to unauthorized users
- No one accountable for data quality
- Compliance violations and audit findings
- Decisions based on unreliable data
With Governance
- Consistent metrics across the organization
- Appropriate access controls
- Clear ownership and accountability
- Compliance requirements met
- Trusted data for decision-making
Data Governance Framework
Policies
High-level principles and rules:
- Data classification policy
- Access control policy
- Retention policy
- Privacy policy
- Quality standards
Processes
How policies are implemented:
- Data quality monitoring
- Access request workflow
- Issue escalation
- Change management
- Compliance auditing
Roles
Who is responsible:
- Data Owner: Business accountability for data
- Data Steward: Day-to-day data management
- Data Custodian: Technical implementation
- Data Consumer: Users of the data
Standards
Specific requirements:
- Naming conventions
- Data formats
- Quality thresholds
- Documentation requirements
- Security controls
Key Governance Domains
Data Quality
Ensuring data is fit for use:
- Accuracy: Is it correct?
- Completeness: Is anything missing?
- Consistency: Do sources agree?
- Timeliness: Is it current?
- Validity: Does it conform to rules?
Data Security
Protecting data from unauthorized access:
- Authentication (who are you?)
- Authorization (what can you access?)
- Encryption (protect data in transit/at rest)
- Audit logging (track all access)
Data Privacy
Handling personal and sensitive data:
- Consent management
- Data minimization
- Purpose limitation
- Individual rights (access, deletion)
- Regulatory compliance (GDPR, CCPA)
Data Lifecycle
Managing data from creation to deletion:
- Creation/acquisition
- Storage and maintenance
- Usage and sharing
- Archival
- Destruction
Metadata Management
Information about your data:
- Data dictionaries
- Lineage tracking
- Business glossaries
- Technical catalogs
Governance for Finance Teams
Financial data has specific governance needs:
Regulatory compliance: SOX, SEC, tax authority requirements
Audit readiness: Documentation and controls for auditors
Segregation of duties: Appropriate access controls
Data lineage: Trace numbers back to source
Change control: Manage modifications to financial data
Retention: Keep data for required periods
Governance Without Bureaucracy
Governance doesn’t have to mean bureaucracy:
Start small: Govern critical data first, expand over time
Automate enforcement: Build controls into systems
Enable, don’t block: Make the right thing easy to do
Clear ownership: Single accountable owner per data domain
Practical policies: Rules people can actually follow
Measure outcomes: Track quality, not just compliance
How Go Fig Supports Data Governance
Go Fig builds governance into the platform:
Semantic layer: Single source of truth for metric definitions
Access controls: Role-based permissions for data access
Audit logging: Track every query and change
Data catalog: Document what data exists and what it means
Lineage tracking: See where data comes from
Quality monitoring: Automatic checks for data issues
Governance is built-in, not bolted on.