About the Course

Organizations increasingly depend on data for service delivery, operational control, regulatory compliance and strategic decision-making. However, fragmented ownership, inconsistent definitions, weak quality controls and unclear decision rights often prevent data from being managed as a reliable institutional asset. Effective data governance provides the authority, accountability and oversight required to address these weaknesses.

This course introduces the principles, structures and processes required to establish a practical data governance programme. It covers governance scope, operating models, roles, policies, standards, data classification, data quality oversight, issue management and performance monitoring. Relevant concepts from DAMA-DMBOK, DCAM and ISO/IEC 38505 are considered without positioning the programme as certification preparation.

Participants will assess an organizational data-governance environment and develop foundation tools that can be adapted to their workplaces. These include a governance charter, accountability matrix, data-policy register, preliminary data inventory, issue-escalation workflow and 90-day implementation plan.

Target Participants

This course is designed for data managers, business analysts, information management professionals, IT managers, compliance and risk officers, monitoring and evaluation professionals, records managers, project managers and departmental representatives who support organizational data responsibilities or are entering data-governance roles.

What You Will Learn

By the end of the course, participants will be able to:

• Distinguish data governance from data management, information governance and cybersecurity
• Define an appropriate organizational data-governance scope
• Compare recognized data-governance frameworks
• Design a foundation data-governance operating model
• Assign data ownership and stewardship responsibilities
• formulate data-governance policies and standards
• Assess priority data assets and governance risks
• Establish data-issue escalation and resolution processes
• Develop indicators for monitoring governance performance
• Prepare a 90-day data-governance implementation plan

Course Duration

• Classroom – 5 Days
• Online – 7 Days

Course Outline

Data Governance Context and Principles

• Data as an organizational asset
• Business drivers for data governance
• Data governance terminology
• Data governance principles
• Data value and institutional risk
• Characteristics of effective governance

Data Governance Scope

• Organizational governance boundaries
• Business data domains
• Structured data coverage
• Unstructured data coverage
• Data lifecycle coverage
• Governance interfaces with existing functions

Data Governance Frameworks

• DAMA-DMBOK governance concepts
• DCAM capability perspective
• ISO/IEC 38505 governance principles
• Data-governance framework selection
• Regulatory alignment requirements
• Organizational framework adaptation

Data Governance Operating Models

• Centralized governance model
• Federated governance model
• Decentralized governance model
• Data governance council structure
• Data domain governance structure
• Governance decision authority

Data Governance Roles and Accountability

• Executive sponsorship responsibilities
• Data owner responsibilities
• Data steward responsibilities
• Data custodian responsibilities
• Data governance office responsibilities
• Accountability assignment using RACI

Data Governance Policies and Standards

• Data policy hierarchy
• Data standard requirements
• Data procedure alignment
• Policy ownership and approval
• Policy exception management
• Policy review cycles

Data Asset Classification

• Data asset identification
• Data inventory structure
• Business data categorization
• Sensitivity classification
• Critical data identification
• Data classification ownership

Data Quality Governance

• Data quality dimensions
• Data quality accountability
• Critical data elements
• Data quality rule definition
• Data quality issue thresholds
• Data quality performance indicators

Data Governance Issue Management

• Governance issue identification
• Issue severity assessment
• Issue ownership assignment
• Escalation threshold definition
• Corrective action tracking
• Issue closure evidence

Data Governance Performance and Improvement

• Data-governance performance indicators
• Governance reporting requirements
• Governance dashboard structure
• Management review responsibilities
• Governance maturity monitoring
• Continuous improvement priorities

Practical Outputs

Participants will develop the following tangible outputs during the programme:

• A foundation data-governance charter
• A data-governance accountability matrix
• A preliminary organizational data inventory
• A data-policy and standards register
• A data-governance issue register
• A 90-day data-governance implementation plan

Training Approach

The course uses facilitator-guided analysis, organizational scenarios, governance-model comparisons, data-domain mapping, policy-review exercises and structured tool-development workshops.

Organizational Benefits

• Clearer accountability for organizational data assets
• Better-defined data-governance decision rights
• Stronger alignment between data policies and operational processes
• More consistent identification of critical and sensitive data
• Improved escalation of data-quality and governance issues
• More reliable evidence of governance activity
• A practical starting plan for institutional data governance

Certification

Participants who successfully complete this course will receive a Certificate of Course Completion from Devimpact Institute, recognizing the knowledge, practical skills and competencies developed through the programme.

Tailor-Made Course

This course can be customized and delivered as an in-house programme to address the specific policies, systems, sector context and capacity-development priorities of an organization. The course duration, modules, case studies and practical exercises may be adjusted following a training needs assessment.