(Data Governance Consultation & Implementation)

Source: DAMA Wheel Evolved - DAMA-DMBOK 2ND EDITION

DATA GOVERNANCE

Data governance is a set of policies, processes, and practices that ensure the effective management of an organization's data assets. It involves defining data standards, assigning data ownership, and implementing controls to protect data quality, security, and integrity.

Data governance typically involves the following components:

  • Data Strategy: Defining the organization's data vision and goals.
  • Data Policies and Standards: Establishing policies and standards for data management, security, and quality.
  • Data Ownership: Assigning responsibility for data management to specific individuals or teams.ะ
  • Data Stewardship: Ensuring that data is used appropriately and in accordance with established policies.
  • Data Security: Implementing measures to protect data from unauthorized access, disclosure, alteration, loss, or destruction.
  • Data Quality Management: Ensuring that data is accurate, complete, and consistent.
  • Data Retention and Deletion: Establishing policies for retaining and deleting data.
  • Data Privacy: Protecting personal data in accordance with applicable laws and regulations.

DATA GOVERNANCE PROCESS IMPLEMENTATION

ASSESSMENT AND GAP ANALYSIS

  • Identify Current State: Conduct a thorough assessment of the organization's existing data governance practices and policies.
  • Identify Gaps: Compare the current state with best practices and regulatory requirements to identify areas for improvement.น
  • Prioritize Risks: Assess the potential risks associated with data governance deficiencies and prioritize areas for action.
  • Define Objectives: Establish clear objectives for data governance, such as improving data quality, enhancing decision-making, and mitigating risks.
  • Develop Policies and Procedures: Create policies and procedures for data governance, including data classification, access controls, retention, and deletion.
  • Assign Roles and Responsibilities: Define the roles and responsibilities of individuals involved in data governance.

DEVELOP A DATA GOVERNANCE FRAMEWORK)

IMPLEMENT DATA GOVERNANCE CONTROLS

  • Data Inventory and Classification: Develop a comprehensive inventory of data assets and classify them according to sensitivity and value.
  • Data Quality Management: Implement processes for ensuring data accuracy, completeness, and consistency.
  • Data Access Controls: Restrict access to data based on roles and permissions.
  • Data Retention and Deletion: Establish policies for retaining and deleting data in accordance with legal and business requirements.
  • Data Security Measures: Implement technical and organizational measures to protect data from unauthorized access, disclosure, alteration, loss, or destruction.

(TRAINING AND AWARENESS)

  • Develop Training Materials: Create training materials that address data governance concepts and best practices.
  • Conduct Training Sessions: Deliver training sessions to employees at all levels to raise awareness of data governance issues and responsibilities.
  • Ongoing Training: Provide ongoing training and updates to keep employees informed of changes in data governance practices and regulations.
  • Regular Monitoring: Continuously monitor compliance with data governance policies and procedures.
  • Internal Audits: Conduct regular internal audits to assess the effectiveness of data governance measures.
  • Management Review: Report on data governance performance to senior management and obtain their support.

MONITORING AND REVIEW

CONTINUOUS IMPROVEMENT

  • Identify Areas for Improvement: Continuously identify areas where data governance practices can be enhanced.
  • Implement Corrective Actions: Take appropriate measures to address identified deficiencies.
  • Review and Update Policies: Regularly review and update data governance policies and procedures to reflect changes in business needs or regulatory requirements.
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