Master Data Management (MDM)

Master Data Management (MDM)

1. Why?

   • Inconsistencies across organization
   • Mergers and acquisitions

2. A set of processes and tools that consistently define and manage the non-transactional data entitiesof an organization

3. Domains

   • Customer
     • Comes from multiple sources
     • The ownership is distributed among multiple customer-facing personnel, and data governance may be centralized or globally distributed.
   • Product
     • Generated internally and shared externally with suppliers.
     • Requires a “hierarchical” data model
     • The ownership is distributed among a number of subject-matter experts while governance is centralized with workflows that manage the changes to master data.
   • Location
   • Employee
   • Asset
   • Financial Entities

4. Governance Rules

   • Origins
     • Source of data and where it was authored
   • Use
     • Who uses it
   • Transformations
     • Lineage
   • Data Model
     • Entity types, attributes, relationships and hierarchies

5. Drivers

   • Why?
     • Improve Business Processes
     • Create Efficiencies
     • Enhance Decision Making
   • What?
     • Improve Reporting and Analytics
     • Single View of the domains

6. Structure

   • Some hierarchical
   • Some web-like

7. Stewardship

   • Who owns the data?

8. Change Managment

   • Version Control
     • Tools
       • Git
       • SVN

9. Workflow approval

   • Who approves?

10. Tools

    • Talend MDM
      • Model-driven
        • Where do we draw the line between each component of Data Quality?
      • Central hub
      • Changes need to be pushed to cloud periodically