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Implementing Reference & Master Data

Master Data projects can easily fail without a plan

  1. Are you involved in a Reference and Master Data project?
  2. Do you know where to start?
  3. Are you struggling to identify the Data sources?
  4. Do you have any idea of the Data Quality in your sources?
  5. Are you aware of the risks & challenges that could derail the project?
If you're nodding along to these questions, you're not alone — Master Data Management projects are notoriously difficult to get right, and most fail not because of technology, but because the people, processes, and governance around it were never properly designed. This course gives you a practical, structured approach to delivering a successful MDM solution, grounded in DAMA DMBoK theory and real-world experience, so you can move from uncertainty to a clear plan of action.
Training Coach sitting

Public courses (online)

Duration: 18 hours
Delivery: 2 options
Full-time for 3 consecutive days
Part-time, one 3-hour session / week, for 6 weeks

Courses are run at different times for these zones:
Central and Eastern Standard Time (CST, EST)
Atlantic Standard Time and Greenwich Meantime (AST, GMT),
Central and Eastern European Time (CET, EET),
Gulf Standard Time (GST)

Private training (online or in-house)

Duration: 18 hours
Full-time over 3 consecutive days, or scheduled as per requirements

*Discounts for groups of +10

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Course overview

This course will prepare you to deliver a successful Master Data Management Solution, teaching you how to combine people, process and technology to create a sustainable solutions. Technology alone does not solve master data problems, the solution requires the creation of processes and roles to address the different aspects of MDM, including Data Governance, Data Quality.

The course covers the following:

  • An introduction to Data Management, within the context of Reference and Master Data
  • Reference and Master Data – the theory according to DAMA DMBoK
  • Applying Data Architecture and Data Modeling techniques to your Master Data implementation
  • How you Master Data Management Implementation needs all Data Management Disciplines
  • Develop an approach and process to suit your specific Master Data Requirements
  • Some practical real-life experience
  • An overview of the technology to assist you, including AI, what the tools can do, and some of the products available.

In addition, the Course is aligned to DAMA DMBoK and will help you prepare to write the DAMA CDMP exam and receive your Reference & Master Data Specialist Certification.

Learning outcomes

After attending this course, you will be able to:

  • Identify the requirements for implementing an MDM Solution
  • Identify, understand, and manage the risks of implementing an MDM solution
  • Identify and define the Architecture, Data Modeling, Data Storage, and Integration aspects of implementing MDM
  • Identify and implement the processes to resolve Data Quality Issues
  • Define and implement an Integration Process with the appropriate Audit Controls
  • Register to write the DAMA CDMP Reference & Master Data Specialist Certification Exam.

Implementing an MDM system can be a game changer for organisations. However, you need to be clear on what the business aims to achieve with the MDM solution.

* A certificate of attendance will be provided on completion of the course

Intended participants

This course will be of interest to people dealing with Masterdata Management:

  • Data Architects
  • Data Stewards
  • Business Analysts
  • Data Analysts
  • Developers
  • DBAs

Why train your team together?

Training a team together creates organisational capability. Transform learning into a shared operational improvement initiative — not just a once-off course.

When teams learn together:

  • Shared understanding of data quality standards and terminology
  • More consistent data practices across the organisation
  • Improved collaboration on data issues and reporting
  • Easier implementation of new data quality processes
  • Stronger accountability and ownership
  • Better communication between business and technical teams
  • Teams return aligned, motivated, and ready to execute

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