Essential Reference and Master Data Management
DATE: April 12, 2022
TIME: 2 PM Eastern / 11 AM Pacific
PRICE: Free to all attendees
About the Webinar
Data tends to pile up and can be rendered unusable or obsolete without careful maintenance processes. Reference and Master Data Management (MDM) has been a popular Data Management approach to effectively gain mastery over not just the data but the supporting architecture for processing it. This webinar presents MDM as a strategic approach to improving and formalizing practices around those data items that provide context for many organizational transactions: its master data. Too often, MDM has been implemented technology-first and achieved the same very poor track record (one-third succeeding on-time, within budget, and achieving planned functionality). MDM success depends on a coordinated approach typically involving Data Governance and Data Quality activities.
Learning objectives:
- Understand foundational reference and MDM concepts based on the Data Management Body of Knowledge (DMBOK)
- Understand why these are an important component of your Data Architecture
- Gain awareness of Reference and MDM Frameworks and building blocks
- Know what MDM guiding principles consist of and best practices
- Know how to utilize reference and MDM in support of business strategy
About the Speaker
Peter Aiken, an acknowledged Data Management (DM) authority, is an Associate Professor at Virginia Commonwealth University, past President of DAMA International, and Associate Director of the MIT International Society of Chief Data Officers. For more than 35 years, Peter has learned from working with hundreds of Data Management practices in 30 countries. Among his 10 books are the first on CDOs (the case for data leadership), the first describing the use of monetization data for profit/good, and the first on modern strategic data thinking. International recognition has resulted in an intensive schedule of events worldwide. Peter also hosts the longest-running DM webinar series (hosted by dataversity.net). From 1999 (before Google, before data was big, and before Data Science), he founded Data Blueprint, a consulting firm that helped more than 150 organizations leverage data for profit, improvement, competitive advantage, and operational efficiencies. His latest venture is Anything Awesome.
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