Purpose
The Data Council governs enterprise-wide data management, ensuring that data is treated as a strategic asset. Its purpose is to establish consistent policies, standards, and best practices for data governance; provide oversight and accountability for data-related initiatives; enable the business to make data-driven decisions by ensuring data is accessible, reliable, and aligned with organisational objectives; and act as the forum where critical data-related issues, risks, and opportunities are identified, prioritised, and resolved.
Without clear ownership and governance, data becomes fragmented, inconsistent, and unreliable — leading to duplicated effort and wasted resources, poor decision-making due to a lack of trusted data, compliance and regulatory risks, and a limited ability to scale advanced analytics and AI.
The Data Council exists to address these challenges by:
- Defining enterprise-wide standards and policies for data management
- Ensuring alignment of data initiatives with business strategy
- Providing a mechanism for balancing competing priorities across functions
- Creating a culture of accountability and stewardship for data
Attendees
Senior representatives from:
- Sales
- Marketing
- Ops
- Content
- Finance
- Technology
Input
- Data Strategy & Prioritisation
- Data Quality
- Taxonomies
- Data Policies & Compliance
- Roles & Responsibilities
Output
The Data Council will deliver:
- A prioritised enterprise data roadmap
- Improved data quality and reduced duplication
- Shared taxonomies and consistent data definitions
- Stronger compliance and risk management posture
- Enhanced ability to drive innovation, analytics, and AI with trusted data
Responsibilities
- Set strategic direction for data initiatives in alignment with business objectives
- Define criteria for prioritising data-related projects (e.g., regulatory compliance, business value, risk mitigation)
- Approve and oversee the roadmap for company data initiatives
- Establish data quality standards and metrics
- Monitor and address systemic data quality issues
- Ensure data owners and stewards are accountable for data accuracy, completeness, timeliness, and consistency
- Provide escalation paths for unresolved data quality concerns
- Define and maintain standard business taxonomies, data definitions, and reference data
- Ensure consistency of critical data elements across systems and functions
- Approve changes to enterprise data definitions and classifications
- Establish and maintain policies for data usage, security, and privacy
- Ensure compliance with regulatory requirements (e.g., GDPR, PDPL)
- Guide ethical data use
- Assign clear ownership of data domains (owners, stewards, custodians)
- Promote accountability for data governance within the business
- Act as the escalation and decision-making body for cross-divisional data issues