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Abstract Blue Light
Certified Data Governance Professional (DGP-805)

Target Students​

Data governance professionals, data stewards, compliance officers, and IT managers responsible for establishing and enforcing data governance frameworks within their organizations.

Duration :  40 hours (5 days)
Learning Objectives

-Understand the principles and practices of data governance.

-Learn how to design and implement effective data governance frameworks.

-Gain skills in managing data stewardship, ownership, and compliance.

-Develop strategies to ensure data quality, integrity, and regulatory compliance.

-Prepare for certification exams and real-world data governance challenges.

Exam Codes: DGP-805
Exam Formats​
 

100 multiple-choice questions

Exam Options​
 

Online

In-Person

Exam Duration: 2 hours
Passing Score​​: 70% 

Course Outline

Foundations of Data Governance
​
Module 1: Introduction to Data Governance
​

  • Understanding Data Governance

  • Definition and Importance of Data Governance in Modern Organizations

  • The Role of Data Governance in Ensuring Data Quality, Security, and Compliance

  • Key Components of a Data Governance Framework

  • Data Governance Frameworks and Models

  • Overview of Common Data Governance Frameworks: DAMA-DMBOK, CMMI, and ISO Standards

  • Developing a Customized Data Governance Framework for Your Organization

  • Case Study: Successful Implementation of a Data Governance Framework

​Module 2: Data Stewardship and Ownership
​

  • Defining Data Stewardship

  • The Role of Data Stewards in Data Governance

  • Responsibilities of Data Stewards: Data Quality, Security, and Compliance

  • Setting Up Data Stewardship Programs within an Organization

  • Data Ownership and Accountability

  • Understanding Data Ownership: Legal and Operational Aspects

  • Assigning Data Ownership and Ensuring Accountability

  • Case Study: Implementing Data Stewardship and Ownership in a Global Corporation

Data Governance Policies and Procedures
Module 3: Developing Data Governance Policies
​

  • Creating Data Governance Policies

  • Key Considerations in Policy Development: Objectives, Scope, and Stakeholders

  • Writing Effective Data Governance Policies: Templates and Examples

  • Ensuring Alignment with Business Objectives and Regulatory Requirements

  • Implementing Data Governance Policies

  • Steps for Rolling Out Data Governance Policies Across the Organization

  • Communicating Policies to Stakeholders: Training and Awareness Programs

  • Monitoring and Enforcing Compliance with Data Governance Policies

Module 4: Data Governance Procedures and Workflows
​

  • Establishing Data Governance Workflows

  • Designing Workflows for Data Access, Sharing, and Management

  • Implementing Approval Processes for Data Usage and Modifications

  • Automation of Data Governance Workflows: Tools and Technologies

  • Operationalizing Data Governance

  • Integrating Data Governance into Daily Business Operations

  • Metrics and KPIs for Monitoring Data Governance Effectiveness

  • Case Study: Operationalizing Data Governance in a Multinational Organization

Data Quality Management
Module 5: Data Quality Frameworks
​

  • Understanding Data Quality in the Context of Governance

  • Dimensions of Data Quality: Accuracy, Completeness, Consistency, Timeliness

  • Establishing a Data Quality Framework within the Data Governance Structure

  • Tools and Techniques for Assessing and Ensuring Data Quality

  • Data Quality Metrics and Monitoring

  • Defining Data Quality Metrics: KPIs and Dashboards

  • Continuous Monitoring and Reporting on Data Quality

  • Case Study: Improving Data Quality Through Governance in a Financial Institution

Module 6: Data Classification and Metadata Management
​

  • Data Classification

  • Importance of Data Classification in Governance and Compliance

  • Implementing Data Classification Schemes: Sensitive, Confidential, Public Data

  • Case Study: Data Classification and Its Role in Regulatory Compliance

  • Metadata Management

  • The Role of Metadata in Data Governance

  • Implementing a Metadata Management Strategy: Tools and Best Practices

  • Using Metadata to Improve Data Discovery, Lineage, and Governance

Compliance, Risk Management, and Security
Module 7: Compliance, Risk Management, and Security
​

  • Understanding Data-Related Regulations

  • Overview of Global Data Privacy and Protection Laws: GDPR, CCPA, HIPAA

  • Ensuring Compliance with Regulatory Requirements

  • Legal Implications of Data Governance: Contracts, SLAs, and Liability

  • Implementing Compliance Programs

  • Developing a Compliance Program Aligned with Data Governance Policies

  • Tools for Monitoring and Reporting Compliance

  • Case Study: Achieving Regulatory Compliance in a Highly Regulated Industry

Module 8: Risk Management in Data Governance
​

  • Identifying and Assessing Data Governance Risks

  • Common Risks in Data Governance: Data Breaches, Non-Compliance, Data Loss

  • Risk Assessment Techniques: Qualitative and Quantitative Approaches

  • Developing a Data Governance Risk Management Plan

  • Data Security and Access Control

  • Implementing Security Controls within the Data Governance Framework

  • Ensuring Secure Data Access and Usage: Role-Based Access Control (RBAC), Encryption

  • Case Study: Mitigating Data Governance Risks in a Large-Scale Organization

Advanced Topics and Capstone Project
Module 9: Advanced Data Governance Strategies
​

  • Governance for Big Data and Cloud Environments

  • Challenges of Implementing Data Governance in Big Data and Cloud Contexts

  • Strategies for Governing Unstructured and Semi-Structured Data

  • Case Study: Data Governance in a Cloud-Based Data Warehouse

  • Ethical Data Governance

  • Addressing Ethical Considerations in Data Governance

  • Developing an Ethical Data Governance Framework

  • Case Study: Implementing Ethical Data Governance in AI and Machine Learning Projects

Module 10: Capstone Project and Exam Preparation
​

  • Capstone Project

  • Participants Work on a Comprehensive Data Governance Project

  • Application of Skills Learned: Policy Development, Compliance, Data Quality, and Risk Management

  • Peer Review and Feedback on Project Work

  • Exam Preparation and Review

  • Review of Key Concepts Covered During the Course

  • Sample Exam Questions and Discussion

  • Final Q&A Session and Wrap-Up

Module 10: Capstone Project and Exam Preparation
​

  • Capstone Project

  • Participants Work on a Comprehensive Data Governance Project

  • Application of Skills Learned: Policy Development, Compliance, Data Quality, and Risk Management

  • Peer Review and Feedback on Project Work

  • Exam Preparation and Review

  • Review of Key Concepts Covered During the Course

  • Sample Exam Questions and Discussion

  • Final Q&A Session and Wrap-Up

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