Certified Data Professional Management CDMP

Overview

Introduction:

This program is designed to prepare participants for the certification exam only.

The Certified Data Management Professional (CDMP) credential represents a globally recognized standard of excellence in data management. It validates advanced capabilities in data governance, quality, modeling, integration, and strategy implementation. This training program provides participants with structured knowledge across core areas of data management, and equips them with analytical and institutional frameworks to manage data as a strategic organizational asset.

Program Objectives:

By the end of this program, participants will be able to:

Analyze governance frameworks and data quality management models.
Explore advanced data modeling and integration methodologies.
Evaluate data security, privacy, and compliance structures.
Use data strategies aligned with institutional and business goals.
Prepare effectively for the CDMP certification exam.

Targeted Audience:

Data Management Professionals.
Data Analysts and Data Scientists.
IT and Data Governance Specialists.
Project Managers with a focus on data initiatives.

Program Outline:

Unit 1:

Data Governance and Quality Management:

Frameworks of data governance based on DAMA-DMBOK and ISO standards.
Institutional models of data ownership and stewardship.
Dimensions and metrics of data quality within enterprise systems.
Linkages between governance structures, compliance, and risk management.
Maturity models for assessing organizational data practices.

Unit 2:

Data Modeling, Design, and Integration:

Structures of conceptual, logical, and physical data models.
Methodologies for ER modeling, dimensional modeling, and NoSQL modeling.
Standards of interoperability across heterogeneous data environments.
Frameworks of ETL processes and data pipeline architectures.
Tools and techniques supporting enterprise data integration.

Unit 3:

Data Security, Privacy, and Interoperability:

Institutional structures for safeguarding sensitive and critical data.
Policies, encryption standards, and control mechanisms in data security.
Global privacy regulations GDPR, CCPA, and HIPAA.
Frameworks for data sharing and interoperability standards.
Balance between data availability, confidentiality, and compliance.

Unit 4:

Data Strategy Implementation and Business Alignment:

Linkages between data management and enterprise strategic planning.
Mechanisms of stakeholder engagement and change management.
Institutional role of data stewardship in strategy execution.
Techniques for organizational data quality enhancement.
Alignment of KPIs and monitoring systems with business value.

Unit 5:

Certification Exam Preparation:

Overview of the Certification Exam Structure.
Key Topics and Areas of Focus for the Exam.
Sample Questions and their potential answers.
Resources and Materials for Effective Exam Preparation.