CERTIFIED DATA MANAGEMENT PROFESSIONAL (CDMP)

Available Dates & Locations

Dates
May 12, 2025
May 16, 2025
Location
Duration
5 Days
Venue

09:00 am – 03:30 pm (Dubai)

Language
Fees

$5,450.00

Dates
May 12, 2025
May 16, 2025
Location
Duration
5 Days
Venue

09:00 am – 03:30 pm (Dubai)

Language
Fees

$3,850.00

Dates
November 17, 2025
November 21, 2025
Location
Duration
5 Days
Venue

09:00 am – 03:30 pm (Dubai)

Language
Fees

$5,450.00

Dates
November 17, 2025
November 21, 2025
Location
Duration
5 Days
Venue

09:00 am – 03:30 pm (Dubai)

Language
Fees

$3,850.00

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COURSE OVERVIEW

The Certified Data Management Professional (CDMP) credential is awarded to those who qualify based on a combination of criteria including education, experience, and test-based examination of professional level knowledge. This credential is offered at the Mastery or Practitioner level. To maintain certified status and continued use of the credential, an annual re-certification fee along with a 3-year cycle of continuing education and professional activity is required. The Data Management Association International (DAMA) authorizes the Certified Data Management Professional certification program and granting of the CDMP designation in partnership with the Institute for Certification of Computing Professionals (ICCP), which administers testing and re-certification. This document outlines the requirements for obtaining the CDMP.

COURSE OBJECTIVES

By completely attending this course, participants will be able to:

  • Apply key concepts of Data Management in the organization.
  • Recommend data security.
  • Manage data quality.
  • Manage data for organizational change.
  • Design data model.
certified data management professional (cdmp)

TARGET COMPETENCIES

  • Data Management Essential Concepts
  • Data Management Framework
  • Data Handling
  • Data Governance
  • Data Architecture
  • Data Modeling and Design
  • Data Storage and Operation
  • Data Security
  • Data Integration and Interoperability
  • Document And Content Management
  • Data Warehouse and Business Intelligence
  • Metadata Management
  • Data Quality
  • Big Data and Data Science
  • Data Management Maturity
  • Data Management and Organization Chance Management

This course is designed for Data Professional Work Experience who has minimum of 2 years’ experience in data management, for those who want to recertify, and professionals who are looking for continuing education in Data Management domain.

This course is an instructor led, participant will be required to complete exercises, case studies individually and in groups.

INTRODUCTION

  • Business Drivers.
  • Goals.

ESSENTIAL CONCEPTS

  • Data and Information.
  • Data as an Organizational Asset.
  • Data Management Principles.
  • Data Management Challenges.
  • Data Management Strategy.

DATA MANAGEMENT FRAMEWORKS

  • 3.1 Strategic Alignment Model.
  • The Amsterdam Information Model.
  • The DAMA-DMBOK Framework.
  • DMBOK Pyramid (Aiken).
  • DAMA Data Management.

DATA HANDLING

  • Introduction.
  • Business Drivers.
  • Essential Concepts.
    • Ethical Principles for Data.
    • Principles Behind Data Privacy Law.
    • Online Data in an Ethical Context.
  • Risks of Unethical Data Handling.

DATA GOVERNANCE

  • Introduction to Data Governance.
  • Activities.
  • Tools and Techniques.
  • Implementation Guidelines.
  • Metrics.
  • Works Cited.

DATA ARCHITECTURE

  • Introduction to Data Architecture.
  • Activities.
  • Tools.
  • Techniques.
  • Implementation Guidelines.
  • Data Architecture Governance.
  • Works Cited.

DATA MODELING AND DESIGN

  • Introduction to Data Modeling.
  • Activities.
  • Tools.
  • Best Practices.
  • Data Model Governance.
  • Works Cited.

DATA STORAGE AND OPERATIONS

  • Introduction to Data Modeling.
  • Activities.
  • Tools.
  • Techniques.
  • Implementation Guidelines.
  • Data Storage Operation Governance.
  • Works Cited.

DATA SECURITY

  • Introduction to Data Security.
  • Activities.
  • Tools.
  • Techniques.
  • Implementation Guidelines.
  • Data Security Governance.
  • Works Cited.

DATA INTEGRATION AND INTEROPERABILITY

  • Introduction to Data Integration.
  • Data Integration Activities.
  • Tools.
  • Techniques.
  • Implementation Guidelines.
  • DDI Governance.

DOCUMENT AND CONTENT MANAGEMENT

  • Introduction to DCM.
  • Activities.
  • Tools.
  • Techniques.
  • Implementation Guidelines.
  • Document and Content Governance.
  • Works Cited.

REFERENCE AND MASTER DATA

  • Introduction to DCM.
  • Activities.
  • Tools.
  • Techniques.
  • Implementation Guidelines.
  • Organization and Cultural Change.
  • Reference and Master Data Governance.
  • Works Cited.

DATA WAREHOUSE AND BUSINESS INTELLIGENCE

  • Introduction to DW/BI.
  • Activities.
  • Tools.
  • Techniques.
  • Implementation Guidelines.
  • DW/BI Governance.
  • Works Cited.

METADATA MANAGEMENT

  • Introduction to DW/BI.
  • Activities.
  • Tools.
  • Techniques.
  • Implementation Guidelines.
  • Metadata Governance.
  • Works Cited.

DATA QUALITY

  • Introduction to DW/BI.
  • Activities.
  • Tools.
  • Techniques.
  • Implementation Guidelines.
  • Data Quality and Data Governance.
  • Works Cited.

BIG DATA AND DATA SCIENCE

  • Introduction to Big Data and Data Science.
  • Activities.
  • Tools.
  • Techniques.
  • Implementation Guidelines.
  • Big Data and Data Science Governance.
  • Works Cited.

DATA MANAGEMENT MATURITY ASSESSMENT

  • Introduction to DMMA.
  • Activities.
  • Tools.
  • Techniques.
  • Implementation Guidelines.
  • Maturity Management Governance.
  • Works Cited.

DATA MANAGEMENT ORGANIZATION AND ROLE EXPECTATION

  • Introduction.
  • Understand Existing Organization and Cultural Norms.
  • Data Management Organizational Constructs.
  • Critical Success Factor.
  • Build the Data Management Organization.
  • Interactions Between the DMO and Other Data-oriented Bodies.
  • Data Management Role.

DATA MANAGEMENT AND ORGANIZATION CHANCE MANAGEMENT

  • Introduction.
  • Laws of Change.
  • Not Managing a Change: Managing a Transition.
  • Kotter’s Eight Errors of Change Management.
  • Kotter’s Eight Stage Process for Major Change.
  • The Formula for Change.
  • Diffusion of Innovations and Sustaining Change.
  • Sustaining Change.
  • Communicating Data Management Value.
  • Works Cited / Recommended.
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