Diagnostic Answers — DM5-001–012
DM5-001 — A
Why: Data modeling begins with discovering/analyzing/scoping requirements, then representing and communicating them precisely. Physical tables are only a later level.
Distractors: B is too narrow; C limits modeling to documenting existing Metadata; D is technology selection/implementation.
Source: pp. 123–124. Confusion: Data modeling vs physical database design.
DM5-002 — B
Why: Modeling confirms/document perspectives so solutions align with current/future business requirements and supports shared understanding/reuse.
Distractors: Governance is not eliminated; one PDM does not replace all documentation; models are maintained because change continues.
Source: pp. 124–126. Confusion: modeling goals vs implementation promises.
DM5-003 — C
Why: the model makes requirements/definitions explicit so business and IT share precise understanding.
Distractors: it supports—not replaces—discussion; it serves more than DBAs; it is not a financial plan.
Source: pp. 125–126. Confusion: model as communication vs implementation artifact.
DM5-004 — D
Why: Category information classifies/assigns types such as color or status.
Distractors: resource = enduring operational profiles; business event = occurrence; detail transaction = fine-grained interaction data.
Source: pp. 126–127. Confusion: category vs resource vs event vs detail transaction.
DM5-005 — A
Why: Customer, Supplier, Facility, Organization, Account are resource profiles used by operations.
Distractors: categories classify; events record occurrences; detail transactions capture granular interactions.
Source: pp. 126–127. Confusion: resource vs event data.
DM5-006 — B
Why: Orders, invoices, withdrawals, and meetings are business events created as processes occur.
Distractors: categories classify; resources endure; detail transaction is the more granular event/interaction layer.
Source: p. 126. Confusion: business event vs detail transaction.
DM5-007 — C
Why: POS line detail, clickstream, and sensor readings match the fine-grained/high-volume detail transaction class.
Distractors: category/resource are different semantic types; business event is broader than the detailed records emphasized here.
Source: pp. 126–127. Confusion: business event vs detail transaction.
DM5-008 — D
Why: an entity is a thing/type about which the organization collects information.
Distractors: A is a value; B resembles a domain/rule; C is a relationship.
Source: p. 127. Confusion: entity vs attribute vs relationship.
DM5-009 — A
Why: Employee is the entity type; Jane is one entity instance/occurrence.
Distractors: B reverses type/instance; C/D assign the wrong modeling constructs.
Source: p. 128. Confusion: entity vs entity instance.
DM5-010 — B
Why: Chapter 5 names clarity, accuracy, completeness for high-quality definitions.
Distractors: A are technical concerns; C are modeling constructs; D are governance/data concerns but not the named definition trio.
Source: pp. 129–130. Confusion: definition quality vs structural properties.
DM5-011 — C
Why: an attribute is a property/characteristic describing (or identifying/measuring) an entity.
Distractors: A is relationship structure; B is broader scope; D is technology choice.
Source: pp. 130–131. Confusion: entity vs attribute.
DM5-012 — D
Why: domains define allowable values/value structures and promote consistency.
Distractors: they complement rather than replace entities/relationships; ownership is governance; domains are not dimensional-only.
Source: current answer key pp. 139–140. Confusion: attribute vs domain.