CDMP DQ-1220 Syllabus Exam Questions Answers

An address beginning with HTTPS indicates that the website uses an encrypted security layer for communications between the client and server. DAMA-DMBOK2 explicitly identifies HTTPS as a security technology and states that the prefix indicates that a website is equipped with an encrypted security layer.

HTTPS uses TLS to protect information while it is transmitted across the network. Its principal security objectives include confidentiality of the communication channel, integrity of transmitted information, and authentication of the server through digital certificates. This is especially important when transmitting credentials, personal information, payment details, or other sensitive data.

HTTPS does not indicate what database technology the website uses, whether a content management system is installed, whether third-party cookies are present, or whether language-translation functionality exists. Those characteristics are independent of transport-layer encryption.

From a Data Management standpoint, encryption in transit is one component of a broader Data Security framework. Sensitive data must also be protected at rest, appropriately classified, access-controlled, monitored, and governed throughout its lifecycle.

Data Quality also benefits indirectly because integrity protection helps prevent unauthorized alteration of values during transmission.

Reference Topics: DAMA-DMBOK2 Chapter 7 — HTTPS; Encryption; Data in Transit; Authentication; Confidentiality; Integrity.

===============

This is Data Enrichment. Enrichment enhances existing records by adding useful information derived from internal or external sources. The original postal address remains intact, while geographic coordinates are appended to make the customer record more useful for location analysis, logistics, service coverage, route planning, or segmentation.

Enrichment differs from cleansing. Cleansing corrects or standardizes defective data; enrichment adds information that was not previously present. A process may perform both—for example, standardizing an address before passing it to a geocoding service.

External enrichment introduces governance and quality considerations. The organization should assess source reliability, licensing and permitted usage, refresh frequency, match confidence, geographical precision, lineage, and whether enrichment values should be treated as authoritative or derived.

Metadata should record that latitude and longitude were obtained from an external geocoding process rather than directly supplied by the customer. Quality metrics may measure match rate, confidence, completeness, or positional accuracy.

DAMA identifies Data Quality Management as including error detection, cleansing, and enrichment strategies, while Metadata Management supports understanding of lineage, definitions, and usage.

Reference Topics: DAMA-DMBOK2 Chapter 13 — Data Enrichment; Cleansing; Profiling; Metadata Lineage; External Data Sources.

===============

The scenario describes a many-to-many relationship: one Person may use several Addresses, while one Address may be associated with several Persons. In relational modelling, this should be resolved using an associative entity—here, Person Address Usage—between Person and Address. The original many-to-many relationship is thereby replaced with two one-to-many relationships. DAMA-oriented references identify this approach directly under the addition of associative entities.

The associative entity normally contains foreign keys referencing both parent entities and may also contain attributes describing the association itself, such as address type, usage purpose, effective date, end date, or primary-address indicator.

Simply modifying the primary keys of Person or Address does not resolve the semantic relationship. Changing foreign-key role names also changes terminology rather than cardinality. The term “partnership entity” is not the appropriate modelling construct.

This design has important Data Quality consequences. It permits explicit integrity constraints between the association and both parent entities, prevents ambiguous repeated columns, and allows the organization to validate rules such as valid effective periods and permitted address-use types.

Reference Topics: DAMA-DMBOK2 Chapter 5 — Relationships; Cardinality; Associative Entities; Resolving Many-to-Many Relationships; Chapter 13 — Referential Integrity and Consistency.

===============

DAMA-DMBOK2 distinguishes the two concepts according to origination versus authoritative consumption. A System of Record (SoR) is an authoritative system in which data is created, captured, or maintained according to defined rules and expectations. A System of Reference (SoRef) is an authoritative location from which consumers obtain reliable information for transactions or analysis even though that information may have originated elsewhere.

Therefore, option A expresses the essential distinction most accurately. For example, an operational CRM may be the System of Record for customer data because customer information is captured and maintained there. An MDM hub or enterprise data-sharing platform can subsequently become the System of Reference used by other applications, even though the original data was created in the CRM.

This distinction is important for Data Quality and lineage. Consumers need to know where values originated, where authoritative corrections are performed, which system distributes trusted values, and which stewardship process governs conflicts between sources. Metadata should therefore record source lineage, system roles, transformations, and authoritative status.

Option D is incorrect because “System of Record” and “System of Reference” do not correspond respectively to master data and reference data categories. Either architectural role can participate in managing different categories of enterprise data.

Reference Topics: DAMA-DMBOK2 Chapter 10 — System of Record and System of Reference; Trusted Sources; MDM Architecture; Metadata Lineage; Chapter 13 — Data Quality and Reference/Master Data Management.

===============