Certified Data Professional Management

Overview:

Introduction:

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

The Certified Data Management Professional (CDMP) certification program is designed to equip participants with the knowledge and skills required to excel in the field of data management. This comprehensive program covers various aspects of data management, ensuring that participants can effectively manage and utilize data within their organizations. 

Program Objectives:

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

• Understand and apply the principles of data governance and data quality management.

• Develop and implement effective data management strategies and frameworks.

• Utilize data modeling techniques to design and manage data structures.

• Implement data integration and interoperability solutions.

• Apply best practices in data security and privacy management.

Targeted Audience:

• Data Management Professionals.

• Data Analysts and Data Scientists.

• IT Managers and Data Architects.

• Business Intelligence and Data Warehousing Professionals.

• Professionals seeking to enhance their data management skills and obtain CDMP certification.

Program Outlines:

Unit 1:

Data Governance and Quality Management:

• Introduction to Data Governance.

• Data Governance Frameworks and Models.

• Data Quality Dimensions and Metrics.

• Data Stewardship and Roles.

• Data Governance Implementation and Best Practices.

Unit2:

Data Strategy and Frameworks:

• Developing a Data Strategy.

• Data Management Maturity Models.

• Data Management Frameworks.

• Business Alignment and Stakeholder Engagement.

• Data Strategy Implementation and Case Studies.

Unit3:

Data Modeling and Design:

• Fundamentals of Data Modeling.

• Conceptual, Logical, and Physical Data Models.

• Data Modeling Tools and Techniques.

• Data Modeling Standards and Best Practices.

• Case Studies in Data Modeling.

Unit 4:

Data Integration and Interoperability:

• Introduction to Data Integration.

• ETL Processes and Tools.

• Data Interoperability Standards.

• Data Integration Architectures.

• Case Studies in Data Integration.

Unit 5:

Data Security and Privacy Management:

• Introduction to Data Security and Privacy.

• Data Security Frameworks and Models.

• Data Privacy Laws and Regulations.

• Implementing Data Security Measures.

• Best Practices in Data Privacy Management.

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