MDM Primer Training

Course #:WA1726

MDM Primer Training

One of the most valuable assets that your enterprise possesses is your data.  It represents a critical element of your organization’s intellectual property.  The trouble is that for many enterprises, their data is spread across multiple disparate data stores, complete with inconsistent data structures, non-standard naming conventions, duplicate data, and conflicting data representations.

No matter how well your applications, services, business processes, or other technology systems and assets are designed, nothing can cover up or otherwise overcome the limitations of bad data.  Mismanaged data results in conflicting reports, unreliable results, information replication issues, and a host of other problems that require extensive workarounds, patches, and troubleshooting.

Master Data Management (MDM) is an alignment strategy aimed at unifying your organization’s data into a coherent whole.  MDM provides an overarching methodology for resolving data fragmentation.  Data fragmentation results in duplicate data, inconsistent information sets, and stale or out-of-data reports.  MDM addresses all of this from a comprehensive perspective and ensures that your data management strategy aligns with your business objectives.

This course provides foundational knowledge in MDM theory, practice, and key components.  Attendees are provided with a broad survey of Master Data concepts and given an opportunity to explore MDM from multiple angles.  Concepts are reinforced through analysis of real world case studies and group discussion.

Topics

  • Master Data Management Concepts
  • Master Data Management 101
  • The Master Data Value Proposition
  • Real World Case Study Analysis
  • Opportunities and Risks
  • MDM Infrastructure and Tools
  • Key Success Factors
  • MDM Adoption

 
 
Audience
 General audience including business and technology team leadership
 
 
Prerequisites
 There are no formal knowledge pre-requisites
 
 
Duration
 1 day

Outline of MDM Primer Training

Chapter 1. Introduction to Master Data Management

  • Defining Master Data
  • Qualities of Master Data
  • Master Data Management (MDM)
  • Common Causes for Unmanaged Data
  • MDM Domains
  • Industry Standard Domains
  • Using Master Data
  • Common Implementation Styles
  • Consolidation Implementation Style
  • Registry or Federation Implementation Style
  • Coexistence Implementation Style
  • Transactional Hub Implementation Style
  • Summary

Chapter 2. MDM Value Proposition

  • Business Benefits of MDM
  • Benefits of Accurate Data
  • Cost Saving and Efficiency
  • Better Regulation Compliance
  • Better Time to Market
  • Mergers and Acquisitions
  • Summary

Chapter 3. Real Life Case Studies

  • Better Reporting at Nationwide
  • Cost Cutting at Shell Oil
  • Single Customer View for Canon Europe
  • Brinker Gets a New Menu
  • Summary

Chapter 4. MDM Risks

  • Risk Categories
  • Technical Risk – Data Model Standardization
  • Technical Risk – Tools and Infrastructure
  • Technical Risk – Data Architecture
  • Technical Risk – Ignoring the Role of Business Processes
  • Technical Risk – Testing and Validation
  • The Carbon Interfaces
  • Human Risk – Change Management
  • Human Risk – Communication
  • Human Risk – Unrealistic Expectations
  • Human Risk – Funding
  • Summary

Chapter 5. Key Success Factors

  • Business Stakeholder Involvement
  • Data Model Design
  • MDM Governance is Essential
  • Incremental Adoption
  • Summary

Chapter 6. Adoption Road Map

  • Incremental Development
  • Typical Adoption Process
  • MDM Adoption Phase 1
  • MDM Adoption Phase 2
  • MDM Adoption Phase 3
  • MDM Implementation Activities
  • Establish Business Goals
  • Gap Analysis and Project Scope Definition
  • Requirements Analysis and Business Process Design
  • Identifying Master Data
  • Document Governance Policies
  • Define the Metadata
  • Perform Master Object Analysis and Modeling
  • Implement the MDM Architecture
  • Implement Data Services
  • Migrate Legacy Application
  • Summary