Welcome to the DGX Data Governance Framework, a framework designed help making implementing data governance straight forward while ensuring compliance with stringent regulatory standards. Our framework delivers comprehensive guidance, enabling entities to efficiently understand, assess, prioritize, and adeptly navigate the multifaceted realm of data-related risks and opportunities.

Crafted in alignment with the principles of the Data Management Association (DAMA) and compliant with the Australian Prudential Regulation Authority (APRA) standards, the DGX Framework stands as a testament to our commitment to quality, reliability, and regulatory adherence. It facilitates a seamless synthesis of technical and strategic data management aspects, ensuring that executive decision-makers and data teams are unified in their approach to leveraging data as a strategic asset.

The DGX Framework is designed to be flexible, allowing for customization to meet the specific needs and priorities of your organization.

Define

• Information Asset Management: Begin by cataloging your data assets. Understand what data you have, where it resides, and its significance to your organization.
• Data Strategy & Architecture: Develop a data strategy that aligns with your business objectives. Design an architecture that supports this strategy and adapts to technological changes.
• Governance: Assign clear roles and responsibilities for data governance. Establish a governance committee to oversee these efforts.
• Critical Data Elements: Identify the data that is critical to your operations and ensure it is accurately defined and managed.
• Data Literacy & Awareness: Cultivate a data-centric culture. Provide training and resources to enhance data literacy across your organization.
• Data Risk Management: Assess potential data risks and create a plan to manage them. Ensure your strategy covers all aspects of data governance.

Protect

• Access Controls: Implement robust access controls to safeguard your data. Ensure that only authorized personnel can access sensitive information.
• Information Protection Processes: Create comprehensive processes to protect your data throughout its lifecycle.
• Third-Party Management: Establish secure protocols for sharing data with third parties and actively manage the associated risks.
• Data Security: Develop and enforce policies to protect your data against breaches and unauthorized access.

Manage & Use

• Data Quality: Commit to maintaining high data quality. Implement procedures to regularly check and cleanse your data.
• Data Lineage: Keep track of data lineage to ensure the integrity and history of your data are preserved.
• Metadata & Reference Data: Leverage metadata and reference data to improve data usability and consistency.
• Data Modelling: Utilize data modeling to provide structure and meaning to your data, facilitating effective analysis and decision-making.
• Data Ethics and AI Governance: Govern your data and AI with ethics in mind. Ensure responsible use of data and AI technologies.

Share

• Sharing Protocols: Develop clear protocols for data sharing that comply with legal and regulatory requirements, and respect data privacy and security.
• Third-Party Management: Ensure that third parties handling your data adhere to your data governance standards.

Retain & Destroy

• Data Retention: Establish data retention policies that align with legal requirements and business needs.
• Data Destruction & De-Identification: Set up secure processes for data destruction and de-identification to responsibly dispose of data that is no longer needed.

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