Authentic DAMA Certification Exam CDMP-RMD Questions Answers

A catalog where products are organized by category is an example of a taxonomy. Here’s why:

Definition of Taxonomy:

Classification System: Taxonomy refers to the practice and science of classification. It involves organizing items into hierarchical categories based on their relationships and similarities.

Example: In the context of a product catalog, taxonomy is used to classify products into categories and subcategories, making it easier to browse and find specific items.

Application in Product Catalogs:

Categorization: Products are grouped into logical categories (e.g., Electronics, Clothing, Home Appliances) and subcategories (e.g., Smartphones, Laptops, Televisions).

Navigation and Search: Helps users navigate the catalog efficiently and find products quickly by narrowing down categories.

References:

Data Management Body of Knowledge (DMBOK), Chapter 9: Data Architecture

DAMA International, "The DAMA Guide to the Data Management Body of Knowledge (DMBOK)"

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.

References:

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.

Entity resolution is a critical step in the MDM process that identifies whether different data records refer to the same real-world entity. This ensures that each entity is uniquely represented within the master data repository.

Data Model Management:

Focuses on defining and maintaining data models that describe the structure, relationships, and constraints of the data.

Data Acquisition:

Involves gathering and bringing data into the MDM system but does not deal with resolving entities.

Entity Resolution:

This process involves matching and linking records from different sources that refer to the same entity. Techniques such as deterministic matching (based on exact matches) and probabilistic matching (based on similarity scores) are used.

Entity resolution helps in deduplication and ensuring a single, unified view of each entity within the MDM system.

Data Sharing & Stewardship:

Focuses on managing data access and ensuring that data is shared responsibly and accurately.

Data Validation, Standardization, and Enrichment:

Ensures data quality by validating, standardizing, and enriching data but does not directly address entity resolution.