The ______development lifecycle is the best approach to follow for Reference & Master Data efforts.
Answer(s): D
The data-centric development lifecycle is best suited for Reference & Master Data efforts because it prioritizes data integrity, quality, and governance throughout the entire development process. This approach ensures that reference and master data are consistently managed, maintained, and leveraged across various systems and applications.
DMBOK (Data Management Body of Knowledge), 2nd Edition, Chapter 11: Reference & Master Data Management.DAMA International Guide to the Data Management Body of Knowledge (DAMA-DMBOK Guide), 2nd Edition.
The most difficult MDM style to implement data governance is which of following-
Answer(s): E
The registry style is the most difficult MDM style to implement data governance due to its reliance on maintaining a central registry of master data without consolidating data physically. This method makes it challenging to ensure consistent governance across disparate systems since data remains distributed and only loosely connected via the registry.
DMBOK (Data Management Body of Knowledge), 2nd Edition, Chapter 11: Reference & Master Data Management.Master Data Management: Creating a Single Source of Truth by David Loshin.
The easiest MDM style to implement data governance based on controls that can be placed on persistent data is:
The centralized style is the easiest MDM style to implement data governance because it consolidates all master data into a single central repository. This centralization simplifies the application of data governance controls, ensuring consistent data quality, standards, and policies are applied across the organization.
DMBOK (Data Management Body of Knowledge), 2nd Edition, Chapter 11: Reference & Master Data Management.Master Data Management and Data Governance by Alex Berson and Larry Dubov.
What type of interactive system model is most often used for Master Data Management?
Answer(s): A
The hub-and-spoke model is most often used for Master Data Management because it provides a central hub where master data is maintained, while the spokes represent different systems or applications that interact with the hub. This model allows for efficient management, synchronization, and distribution of master data across the enterprise, ensuring consistency and quality.
DMBOK (Data Management Body of Knowledge), 2nd Edition, Chapter 11: Reference & Master Data Management.The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling by Ralph Kimball and Margy Ross.
When 2 records are not matched when they should have been matched, this condition is referred to as:
Answer(s): C
Definitions and Context:False Positive: This occurs when a match is incorrectly identified, meaning records are deemed to match when they should not.True Positive: This is a correct identification of a match, meaning records that should match are correctly identified as matching.False Negative: This occurs when a match is not identified when it should have been, meaning records that should match are not matched.True Negative: This is a correct identification of no match, meaning records that should not match are correctly identified as not matching.Anomaly: This is a generic term that could refer to any deviation from the norm and does not specifically address the context of matching records.The question asks about a scenario where two records should have matched but did not. This is the classic definition of a False Negative.In data matching processes, this is a critical error because it means that the system failed to recognize a true match, which can lead to fragmented and inconsistent data.
DAMA-DMBOK: Data Management Body of Knowledge, 2nd Edition, Chapter 11: Master and Reference Data Management.ISO 8000-2:2012, Data Quality - Part 2: Vocabulary.
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