Diagnostic Answers — DM5-037–048
DM5-037 — A
Why: SCD Type 2 creates a new row/version and preserves history.
Distractors: Type 1 overwrites; Type 3 adds a prior-value column; snowflaking is a dimension-structure choice.
Source: pp. 147–148. Confusion: SCD 1/2/3.
DM5-038 — B
Why: Type 3 stores limited prior state in another column.
Distractors: Type 1 keeps only current; Type 2 adds rows; conformed fact is measure standardization.
Source: pp. 147–148. Confusion: SCD 1/2/3.
DM5-039 — C
Why: a conformed dimension is consistently defined for sharing across dimensional models/marts.
Distractors: it is not forced 3NF, not SCD-only, and does not replace facts.
Source: pp. 147–148. Confusion: conformed dimension vs conformed fact.
DM5-040 — D
Why: Object-Oriented/UML class modeling includes attributes + operations/methods and encapsulation.
Distractors: relational/dimensional/fact-based have different core constructs.
Source: pp. 148–150. Confusion: OO vs relational.
DM5-041 — A
Why: Fact-Based modeling centers objects/facts/roles and controlled verbalization rather than attributes as the primary construct.
Distractors: B = dimensional; C = NoSQL document; D reduces it incorrectly to physical implementation.
Source: pp. 150–151. Confusion: Fact-Based vs attribute-centered models.
DM5-042 — B
Why: Data Vault uses hubs, links, satellites.
Distractors: A = dimensional; C = Anchor; D = graph.
Source: pp. 151–153. Confusion: Data Vault vs Anchor.
DM5-043 — C
Why: Anchor Modeling uses anchors, attributes, ties, knots.
Distractors: A = Data Vault; B = dimensional; D mixes NoSQL concepts.
Source: pp. 152–153. Confusion: Anchor vs Data Vault.
DM5-044 — D
Why: document databases store records as document structures.
Distractors: key-value centers known-key lookup; column organizes by column family; graph centers nodes/relationships.
Source: pp. 153–156. Confusion: NoSQL document vs key-value vs column vs graph.
DM5-045 — A
Why: traversal of highly connected relationships is the defining graph clue.
Distractors: document/key-value/column serve different access shapes.
Source: pp. 153–156. Confusion: graph vs other NoSQL categories.
DM5-046 — B
Why: CDM establishes high-level business concepts/relationships, scope, and vocabulary.
Distractors: indexes/partitions and datatype details are later physical concerns; production tables are not the conceptual purpose.
Source: pp. 156–159. Confusion: conceptual vs logical vs physical.
DM5-047 — C
Why: LDM adds detailed attributes, keys, domains, normalized structure while staying technology-independent.
Distractors: A is too conceptual; B is physical; D confuses data-flow representation.
Source: pp. 156–159. Confusion: logical vs conceptual/physical.
DM5-048 — D
Why: PDM is technology-specific implementation design including database/storage details.
Distractors: A is conceptual/logical; B/C contradict physical model content/timing.
Source: pp. 156–159. Confusion: physical vs logical.