How to Define Master Data (SlideShare version)
Published on Nov 19, 2015
This presentation briefly introduces the complex topic of Master Data Management (MDM) and defining Master Data. The specifics of the endeavor would be subjective to the organization.
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PRESENTATION OUTLINE
Master Data Management is vital in promoting the ability to retrieve accurate, complete, relevant, and timely information.
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A preliminary to implementing MDM is to define Master Data - in two senses:
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1.
Define the meaning of the term Master Data
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2.
Define the data that warrant Master Data Management
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Master Data
David Loshin's "description" of
In her article “Defining Master Data for Your Organization,” (http://www.itbusinessedge.com/cm/blogs/lawson/defining-master-data-for-your...) Loraine Lawson references industry leaders David Loshin of Knowledge Integrity, Inc., and Marty Moseley of IBM. (Loshin refers to his definition as a “description.”)
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"Master data objects represent the core business concepts used in the different applications across the organization...such as customers, suppliers, parts, products, locations, contact mechanisms."
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Supplemented by Marty Moseley
Moseley augmented Loshin’s post with his own response.
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First, leaders should determine their organization's data-defining "subject areas."
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Then, they should evaluate the data in each subject area against the following three criteria:
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1. The subject area is a building block of critical business transactions.
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2. The data in the subject area are created and managed in multiple systems.
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3. Incorrect, inaccurate, incomplete, mismanaged data in the subject area have the potential to harm the organization.
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Master Data Criteria
Wolter and Haselden's
In their article "The What, Why, and How of Master Data Management," (http://msdn.microsoft.com/en-us/library/bb190163.aspx) Wolter and Haselden discuss eight criteria that should be considered jointly in deciding which data to include in MDM.
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8 Master Data Criteria
1. Behavior
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The interaction between master data and transactional data is analogous to the noun/verb relationship, with master data behaving as the noun and transactional data as the verb.
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2. Life Cycle
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3. Cardinality
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The greater the number of elements in a data set, the greater the need - and advantages - of handling the set as master data.
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4. Lifetime
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The longer the lifespan of an entity, the greater the tendency to treat that entity as master data.
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5. Complexity
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Entities that need MDM are often complicated to manage - having, for example, many attributes to record, track, and update.
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6. Value
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The more significant the element's monetary value to the organization, the more it will justify treatment as master data.
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7. Volatility
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Master data attributes would be subject to a sufficient degree of volatility or change to warrant MDM.
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8. Reuse
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The integrity of data that is shared between departments and across systems should be enforced with a MDM system.
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Neglecting to define and manage Master Data can be costly for an organization.
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