Data Governance

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.