The DMBoK and CDMP Preparation: Data Management Fundamentals course, offered by the British Academy for Training and Development, is a comprehensive program designed to provide participants with the essential concepts and practical methodologies of data management. The course prepares participants to take the Data Management Body of Knowledge (DMBoK) exam and achieve the Certified Data Management Professional (CDMP) certification, which is globally recognized in the field of data management.

The course covers fundamental principles governing data management within organizations, including data governance, data quality, metadata management, data integration, and data security. It also focuses on how to improve data management strategies within organizations and offers practical solutions for the challenges professionals face in this field.

Target Audience

The course is designed for:

• Data management professionals preparing for the CDMP certification exam.

• Data analysts, business analysts, and data architects looking to deepen their foundational knowledge of data management.

• IT professionals responsible for managing and governing data.

• Individuals seeking to advance their careers in the field of data management.

• Managers involved in data-driven decision-making within organizations.

Objectives

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

• Understand the fundamental principles of data management and their practical applications.

• Acquire the knowledge needed to prepare for the DMBoK exam and achieve the CDMP certification.

• Learn how to apply best practices in data quality, data governance, and data security management.

• Be ready to successfully pass the CDMP exam.

• Apply effective strategies to enhance data management within organizations.

• Overview of Data Management

  • Definition of data management and its importance in organizations.

  • Core practices in data management.

  • The relationship between data and technology in the modern world.

• DMBoK Framework

  • An introduction to DMBoK (Data Management Body of Knowledge).

  • Explanation of the ten domains of DMBoK.

  • How to apply DMBoK within organizations.

• Data Governance

  • Definition and importance of data governance.

  • The organizational structure of data governance.

  • Best practices in setting up and implementing data governance policies.

• Data Quality Fundamentals

  • What is data quality and how is it measured?

  • Key dimensions of data quality: accuracy, consistency, and completeness.

  • How to improve data quality within the organization.

• Data Architecture

  • The concept of data architecture and its importance in organizations.

  • Key elements of data architecture.

  • How to design flexible and efficient data structures.

• Data Modeling

  • Introduction to data modeling.

  • Types of data models: conceptual, logical, and physical.

  • The importance of data modeling in quality management and data governance.

• Metadata Management

  • Definition and role of metadata in data management.

  • Different types of metadata: business, technical, and operational.

  • How to effectively manage metadata.

• Data Integration

  • Techniques for integrating data from multiple systems.

  • The importance of ETL (Extract, Transform, Load) in data integration.

  • How to build effective and efficient integrated data repositories.

• Data Security and Privacy

  • The fundamental principles of data security.

  • Best practices to secure data and protect it from threats.

  • Data privacy laws and regulations, such as GDPR, and their impact on data management.

• Master Data Management (MDM)

  • The concept and importance of master data management.

  • How to implement MDM to improve data management across the organization.

  • Best practices for managing master data and ensuring its quality.

• Data Lifecycle Management

  • Stages of the data lifecycle: from creation to deletion.

  • Strategies for managing data throughout its lifecycle.

  • Data retention policies and regulatory compliance.

• Challenges in Master Data Management

  • Challenges related to quality and governance in master data management.

  • How to improve coordination between master data and operational data.

  • Solutions to common problems in master data management.

• Overview of the CDMP Exam

  • Introduction to CDMP (Certified Data Management Professional) certification.

  • The key topics covered in the CDMP exam.

  • Strategies for preparing to pass the CDMP exam successfully.

• Final Review and Exam Preparation

  • Comprehensive review of key concepts.

  • Practice exam questions and mock tests.

  • Tips and strategies for final exam preparation.