I have completed teaching the Master Data Management Course in Sydney.  Thank you to my wonderful students.  Some memorable learning the last 2 days was done around some of these points:

• Master data, with MDM, can be left where it is or, more commonly, placed in a separate hub
• Product MDM tends to be more Governance-heavy than Customer
• In a ragged hierarchy, a node can belong to multiple parents
• Be selective about the fields you apply change management to
• Customer lifetime value should ideally look forward, not behind, and should use profit instead of spend
• Customer analytics can be calculated in MDM or CRM, the debate continues
• Complex subject areas require multiple group input
• Critical elements in MDM data security include confidentiality, integrity, non-repudiation, authentication and authorization
• Syndicated data is becoming increasingly important and MDM is the most leveragable place to put that data
• The web is also a source of syndicated data
• Data quality is a value proposition
• Do you have a data problem or a customer data problem or a product data problem?  It affects your tool selection
• Care about what matters to your shop when you evaluate vendors
• The program methodology should be balanced between rigor and creativity
• In the design phase, you develop your test strategy, data migration plan, non-functional requirements, functional design, interface specifications, workflow design and logical data model
• Don't mess up by staffing the team with only technicians
• The purpose of the data conversion maps is to document the requirements for transforming source data into target data
• Organizational change management is highly correlated to project success
• Stakeholder management is not a one-time activity

Day 1 of The 3-day Master Data Management course is in the books here in beautiful Sydney, Australia.  It's been an outstanding day of learning and sharing about the emerging, important discipline of master data management.

Here are my most vivid recollections from today:

• MDM is highly misunderstood due to the wide range of benefits provided
• MDM is part of major changes in how we handle data and to information chaos, which will get more complex before it gets less complex
• MDM can and should support Hadoop data and all manner of data marts
• Lack of a subject-area orientation in the culture is a challenge for MDM
• Some MDM is analytical, most is operational
• MDM subject areas can mix or hybrid across factors of analytical/operational, physical/virtual and the degree of governance needed
• Often many systems build components of a master record, few work on the same attributes
• MDM returns are in the improved efficacy of projects targeting business objectives
• To do a return on investment justification, all project benefits must be converted to cash flow
• MDM should be tightly aligned with successful projects, creating benefits for the MDM program
• Personal motivators must be understood and are important in building an MDM roadmap
• Vendor solutions may be subject area-focused or support multiple subject areas
• Tactical MDM supports an individual project, enterprise MDM supports the organization for the subject area
• Strong project management discipline can be more important in that role than MDM domain knowledge
• The data warehouse will remain relevant in organizations, but many of its functions are moving operational, such as those to MDM
• You can mix a subject are with the hub persisting frequently used data elements and pointing to source systems with the rest of the data
• Do not count on the data warehouse for what MDM provides
• Governance workflows provide the ability to escalate if actions are not taken in a timely manner
• External sources like EPCID are becoming relevant in the product subject area

More to come on days 2 and 3.