Data Governance

Data is an asset. Governance protects it.

 

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Hunter Storm Data Governance

 

Introduction

Data governance establishes the principles, rules, and controls used to manage data throughout its lifecycle. It defines how data is created, classified, maintained, accessed, validated, retained, and retired to support accuracy, integrity, traceability, security, and appropriate use.

Within the Hunter Storm ecosystem, data governance provides the framework for managing information consistently across systems, records, and artifacts. It supports reliable documentation, controlled vocabularies, classification practices, and the relationships between authoritative records and their associated resources.

 

Purpose and Scope

Data governance applies to data managed within the systems and processes designated by the applicable governance framework. Its scope includes data quality, classification, ownership and stewardship, access, lifecycle management, change control, and compliance with applicable policies and requirements.

 

Governance Principles

• Accuracy: Data should reflect the best available verified information.
• Integrity: Data must be protected against unauthorized or undocumented alteration.
• Consistency: Shared definitions, formats, identifiers, and controlled vocabularies should be applied consistently.
• Traceability: Data origins, relevant changes, and verification status should be documented when applicable.
• Accountability: Responsibility for creating, maintaining, validating, and approving data should be identifiable.
• Security and appropriate access: Data should be handled according to its classification and applicable access controls.
• Lifecycle management: Data should be managed from creation or acquisition through maintenance, retention, archival, and authorized disposition.

 

Data Quality and Validation

Data quality controls should address accuracy, completeness, consistency, validity, and currency as appropriate to the data type and intended use. Validation should identify missing values, conflicting information, malformed records, broken references, and deviations from established schemas or controlled vocabularies.

A failed validation should be documented and resolved when warranted. Unverified information must not be represented as verified merely because it has been recorded.

 

Data Stewardship and Accountability

Responsibilities for data management should be assigned according to the applicable system and governance arrangements. These responsibilities may include data creation, maintenance, validation, access authorization, change approval, and resolution of identified discrepancies.

Where a function is performed by a single individual, the governance documentation should describe the function accurately rather than imply that separate personnel or independent review exist.

 

Classification, Access, and Protection

Data should be classified and handled according to the applicable information-classification framework. Access, disclosure, modification, and distribution should follow the controls and restrictions established for the relevant data and system.

Classification and access decisions should be supported by applicable rules rather than assumptions based solely on the location or format of a record.

 

Change Control and Traceability

Material changes to governed data should be recorded when necessary to preserve an accurate history of the record. Relevant information may include the affected item, the nature of the change, the date, the reason, the responsible party, and the verification or approval status.

Corrections should preserve the distinction between the original record, the corrected state, and any superseding artifact when that distinction is material to the record’s history.

 

Data Lifecycle and Retention

Data should be managed throughout its lifecycle in accordance with applicable retention, archival, preservation, and disposition rules. Lifecycle decisions should account for operational needs, evidentiary value, legal or contractual obligations, and the integrity of associated records.

 

Compliance and Review

Governed data and associated processes should be reviewed against applicable policies, schemas, classification rules, and other established requirements. Identified discrepancies should be documented, assessed, and corrected as appropriate. Completion of a review should not be treated as proof of compliance beyond the scope of the checks actually performed.

 

Relationship to Other Governance Systems

Data governance operates alongside records management, audit and verification, information classification, and system-specific controls. These functions are related but distinct: data governance establishes how data is managed; records management governs the treatment and traceability of records; and audit and verification assess whether specified information or processes meet their applicable criteria.

 

Governance Maintenance

This document should be maintained when material changes occur to the systems, policies, data structures, or requirements within its scope. Revisions should preserve consistency with related governance documents and identify conflicts or dependencies that require resolution.