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DACO practice questions

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Question 1Data Governance and Strategy

In a data governance operating model, what is the primary accountability of a data owner for a defined data domain?

  1. Writing the ETL code that loads the domain data into the warehouse each night
  2. Performing the annual external audit of the organization's financial statements
  3. Configuring the physical storage and backup schedules for the databases holding the domain data
  4. Approving access requests and decisions about quality, definition, and permitted use of the domain data Correct answer.

Explanation

A data owner is the accountable business role for a data domain and decides on access, quality standards, definitions, and permitted use. Technical storage, pipeline development, and external audit are separate operational or assurance roles that support but do not replace that accountability.

Question 2Data Governance and Strategy

A steward discovers that two business units calculate 'active customer' differently in their reports. Which governance artifact is designed to resolve this conflict permanently?

  1. A one-time email to both units asking them to agree informally
  2. A firewall rule restricting access to the customer table
  3. A database index on the customer status column
  4. An approved enterprise data definition with a documented calculation rule and assigned owner Correct answer.

Explanation

Conflicting metric logic is resolved through governed business definitions and calculation rules that are approved, owned, and published for reuse. Informal agreement does not persist, and technical controls such as indexes or firewall rules do not define business meaning.

Question 3Data Governance and Strategy

Which statement best describes the purpose of a data governance charter?

  1. It authorizes the governance program, defines its scope, and records decision rights and reporting lines Correct answer.
  2. It contains the source code for the master data management application
  3. It lists every column in every production database with its data type
  4. It specifies the hardware specification for the analytics cluster

Explanation

A charter is the founding document that legitimizes the program, sets scope and objectives, and clarifies who decides what and how the program reports. Column inventories, infrastructure specifications, and application code are technical artifacts maintained elsewhere.

Question 4Data Governance and Strategy

An organization wants a single cross-functional forum to arbitrate data policy conflicts and prioritize data initiatives. Which body fits this description?

  1. A data governance council with representatives from business, IT, legal, and risk Correct answer.
  2. A help desk team that resets user passwords
  3. A project steering committee for a single software rollout
  4. An external marketing agency

Explanation

A governance council is a cross-functional decision body that resolves policy conflicts and sets priorities across the data program. Password support, single-project steering, and external agencies lack the enterprise mandate and cross-domain membership required.

Question 5Data Governance and Strategy

Which pairing correctly matches a data governance principle with its practical implication?

  1. Timeliness - data is retained indefinitely regardless of legal obligations
  2. Security - all data is made publicly available to maximize reuse
  3. Transparency - data lineage and definitions are documented and accessible to authorized stakeholders Correct answer.
  4. Accountability - no individual is named responsible for any data domain

Explanation

Transparency means stakeholders can see where data comes from and how it is defined, which requires documented lineage and definitions. The other pairings contradict the principles they claim to illustrate.

Question 6Data Governance and Strategy

What distinguishes a data steward from a data owner in most governance operating models?

  1. The steward executes day-to-day quality and definition work on behalf of the accountable owner Correct answer.
  2. The steward holds legal liability for regulatory breaches involving the data
  3. The steward owns the budget for the data platform
  4. The steward approves the enterprise data strategy

Explanation

Stewards perform the operational work of maintaining definitions, monitoring quality, and resolving issues within the direction set by the accountable owner. Legal liability, platform budget, and enterprise strategy sit with other roles.

Question 7Data Governance and Strategy

A regulator asks the organization to demonstrate lawful basis for processing personal data. Which governance capability most directly provides this evidence?

  1. A maintained record of processing activities linked to consent and legal basis Correct answer.
  2. A dashboard showing server CPU utilization
  3. A list of employees who attended a coding bootcamp
  4. The organization's social media content calendar

Explanation

Records of processing activities capture purpose, categories of data, recipients, and legal basis, which is exactly what regulators request as evidence of lawful processing. The other artifacts are unrelated to privacy compliance evidence.

Question 8Data Governance and Strategy

Which metric best indicates whether governed data definitions are actually being adopted across the organization?

  1. Percentage of certified reports and dashboards that reference approved definitions Correct answer.
  2. Average length of a data steward's tenure in the role
  3. Number of database servers provisioned in the data center
  4. Total volume of storage consumed by the warehouse

Explanation

Adoption of definitions is demonstrated when certified reporting assets use the approved terms, so a coverage percentage of certified reports referencing them is a direct adoption measure. Infrastructure and staffing metrics do not show whether definitions are used.

Question 9Data Governance and Strategy

A global retailer wants one authoritative customer record shared by e-commerce, stores, and service. Which governance-led initiative addresses this need?

  1. A master data management program with governed matching rules and a designated customer domain owner Correct answer.
  2. An initiative to shorten the password reset process
  3. A migration of all data to a single physical server
  4. A campaign to increase the number of spreadsheets used by each channel

Explanation

Master data management creates a governed, authoritative record for a domain such as customer, supported by matching rules and clear ownership. Spreading spreadsheets, consolidating hardware, and speeding password resets do not establish a single trusted customer record.

Question 10Data Governance and Strategy

A data governance council must decide whether to fund a metadata catalog or a data quality remediation project with a limited budget. Which approach reflects sound governance decision-making?

  1. Evaluate both options against agreed program objectives, quantified risk reduction, and measurable business value Correct answer.
  2. Defer the decision indefinitely to avoid conflict
  3. Fund the option proposed by the most senior person in the room without analysis
  4. Split the budget equally regardless of expected outcomes

Explanation

Governance decisions should be traceable to objectives and expected value or risk reduction so that trade-offs are defensible. Seniority alone, arbitrary splitting, and indefinite deferral all bypass the evidence-based rationale governance exists to provide.

Question 11Data Governance and Strategy

Which activity is the most appropriate first step when establishing a new data governance program in a large organization?

  1. Publish a policy prohibiting all data sharing across departments
  2. Immediately purchase a governance tool and configure all workflows
  3. Assess current data maturity, pain points, and stakeholder landscape to scope the program Correct answer.
  4. Replace every existing data owner with a central team

Explanation

A maturity and stakeholder assessment establishes scope, priorities, and a baseline against which progress can be measured, which should precede tooling and policy. Buying tools first, banning sharing, and removing owners all act before understanding the environment.

Question 12Data Governance and Strategy

A data owner is asked to approve a new analytics use case involving customer behavior data. Which consideration is central to a defensible approval decision?

  1. Whether the dashboard color scheme matches corporate branding
  2. Whether the requesting analyst has the fastest laptop in the department
  3. Whether the project can be completed before the next holiday
  4. Whether the intended use is consistent with the purpose for which the data was collected and permitted Correct answer.

Explanation

Approval should test purpose compatibility and permitted use, because using data beyond its collected purpose can breach privacy commitments and policy. Hardware, visual design, and scheduling are operational details that do not determine lawful or ethical use.

Question 13Data Governance and Strategy

Which statement correctly describes the relationship between a data policy and a data standard?

  1. A policy and a standard are identical documents with different titles
  2. A policy states mandatory rules and intent, while a standard specifies the concrete requirements that satisfy the policy Correct answer.
  3. A standard states high-level intent, while a policy lists column data types
  4. A policy is optional guidance, while a standard is legally binding legislation

Explanation

Policies express mandatory direction and intent, and standards translate that intent into specific, testable requirements such as formats or classification levels. Reversing the hierarchy or treating them as identical obscures how compliance is achieved.

Question 14Data Governance and Strategy

A business unit wants to onboard a new SaaS vendor that will process personal data. Which governance control should gate the onboarding?

  1. A vendor risk assessment covering data protection terms, security posture, and processing location Correct answer.
  2. A check that the vendor's office is near headquarters
  3. A review of the vendor's logo usage guidelines
  4. An estimate of the vendor's social media follower count

Explanation

Third-party processing requires due diligence on contractual data protection terms, security controls, and where data will be processed, which the governance process should require before approval. Cosmetic, geographic proximity, and popularity checks do not address data risk.

Question 15Data Governance and Strategy

Which element is essential in a data classification scheme used to drive handling controls?

  1. A random assignment of labels to datasets each quarter
  2. Defined sensitivity levels with explicit handling requirements for each level Correct answer.
  3. A single level applied to all data regardless of content
  4. Classification performed only by the external auditor

Explanation

A classification scheme is useful only when levels are defined and each level maps to concrete handling rules such as encryption, access, and retention. Random, uniform, or externally-only classification cannot drive consistent controls.

Question 16Data Governance and Strategy

A governance team finds that critical reports are frequently corrected after publication. Which governance response addresses the root cause most effectively?

  1. Shorten the report publication deadline
  2. Add more colors to the report charts
  3. Increase the number of approvers who sign off on the report layout
  4. Define quality rules and ownership for the source data feeding those reports, with monitoring and issue escalation Correct answer.

Explanation

Post-publication corrections usually trace to defects in source data, so quality rules, accountable owners, and monitored escalation address the cause. Layout approvals, deadlines, and styling affect presentation and timing, not data correctness.

Question 17Data Governance and Strategy

Which practice best supports the governance principle of data minimization in an analytics environment?

  1. Granting broad access so analysts never need to request data
  2. Copying all production tables into a shared sandbox for convenience
  3. Providing analysts with de-identified or aggregated data limited to fields needed for the analysis Correct answer.
  4. Retaining every intermediate dataset indefinitely

Explanation

Minimization means using only the data necessary for the stated purpose, so limiting fields and de-identifying or aggregating reduces exposure while meeting analytical needs. Bulk copying, indefinite retention, and broad access all expand data use beyond necessity.

Question 18Data Governance and Strategy

A new regulation requires the organization to respond to data subject access requests within 30 days. Which governance mechanism best ensures this obligation is met?

  1. A verbal understanding among a few employees
  2. A documented request-handling procedure with named responsibilities, tracked service levels, and periodic testing Correct answer.
  3. An annual reminder email with no assigned owner
  4. A policy statement that requests will be handled whenever convenient

Explanation

Regulatory obligations are met through documented procedures with clear ownership, tracked timelines, and testing to confirm the process works. Informal understanding, ownerless reminders, and discretionary timing cannot reliably meet a fixed legal deadline.

Question 19Data Governance and Strategy

Which characteristic most clearly distinguishes a data domain from a database schema?

  1. A domain is a business subject area with an accountable owner, while a schema is a technical structure in a system Correct answer.
  2. A schema is owned by the legal department and a domain by the vendor
  3. A domain is defined by the database vendor's licensing terms
  4. A domain exists only inside a single application's tables

Explanation

Domains are business-scoped subject areas such as customer or product with accountable ownership, whereas schemas are technical containers defined in a database. Vendor licensing, legal ownership, and application boundaries do not define a domain.

Question 20Data Governance and Strategy

An organization is deciding how to govern a data mesh-style architecture where domains publish data products. Which governance element is most critical to preserve consistency?

  1. Elimination of all central standards so each domain can define its own meaning
  2. A single central team that manually approves every query
  3. Complete prohibition on domain teams publishing data
  4. Federated computational governance with shared global standards enforced through automated policy checks Correct answer.

Explanation

Federated computational governance pairs domain autonomy with globally agreed standards that are enforced automatically, which keeps data products interoperable. Removing standards, manual query approval, and banning publication all defeat the model's purpose.

Question 21Data Governance and Strategy

A data owner approves access to a sensitive dataset for a project, and the project later expands its scope without notifying the owner. Which governance control most directly detects this drift?

  1. Adding more columns to the dataset
  2. Reducing the frequency of audit logging
  3. Increasing the maximum password length for all users
  4. Periodic access recertification that validates each grant against current documented purpose Correct answer.

Explanation

Recertification forces periodic revalidation of every access grant against its documented purpose, which surfaces scope creep. Password length, added columns, and reduced logging do not verify whether access still matches an approved purpose.

Question 22Data Governance and Strategy

A regulator requests evidence that the organization's data governance controls operate effectively over time, not merely that they exist on paper. Which evidence set best satisfies this request?

  1. A copy of the governance policy document alone
  2. Operating effectiveness testing results, exception logs, remediation records, and management sign-offs across periods Correct answer.
  3. A list of planned future initiatives
  4. An organization chart showing governance roles

Explanation

Assurance of operating effectiveness requires evidence that controls ran consistently, including test results, exceptions, remediation, and sign-offs over time. A policy, an org chart, or future plans show design or intent but not that controls actually worked.

Question 23Data Governance and Strategy

Two business units legitimately need different definitions of 'revenue' for statutory reporting and for management analysis. What is the soundest governance resolution?

  1. Force both units to use the management definition for every purpose
  2. Leave both definitions undocumented to preserve flexibility
  3. Register both as distinct governed metrics with explicit scope, owner, and disambiguation in the catalog Correct answer.
  4. Forbid one unit from reporting revenue at all

Explanation

Governance can accommodate multiple legitimate definitions when each is explicitly scoped, owned, and clearly distinguished so consumers know which applies. Banning reporting, forcing one definition everywhere, or leaving ambiguity undocumented creates errors and disputes.

Question 24Data Governance and Strategy

An organization wants to measure whether its data governance program delivers value. Which indicator set is most meaningful?

  1. Count of policy documents stored on the shared drive
  2. Reduction in data incidents, faster issue resolution, increased certified data product reuse, and lower regulatory findings Correct answer.
  3. Number of governance meetings held and slides produced
  4. Total number of employees who have ever heard of the program

Explanation

Value is shown by outcomes such as fewer incidents, quicker resolution, greater reuse of certified assets, and reduced regulatory findings. Activity counts and awareness measures show effort or visibility but not delivered benefit.

Question 25Data Governance and Strategy

A multinational must reconcile a local legal requirement to delete certain records with a global policy requiring long retention for analytics. Which governance approach is most defensible?

  1. Delete all analytics data globally to avoid any conflict
  2. Ignore the local law and follow the global policy everywhere
  3. Apply jurisdiction-specific retention rules that override the global default where law requires, documented in the retention schedule Correct answer.
  4. Store the records without documenting which rule applies

Explanation

Retention schedules should encode legal obligations by jurisdiction so that mandatory local rules take precedence over defaults, with the rationale documented. Ignoring law, over-deleting globally, or leaving rules undocumented creates compliance and analytical harm.

Question 26Data Governance and Strategy

Which artifact sits directly below a data policy in a typical governance hierarchy and translates the policy's intent into measurable, enforceable criteria?

  1. A data quality dashboard
  2. A data standard Correct answer.
  3. A project charter
  4. A data steward roster

Explanation

Governance hierarchies usually place policy at the top, expressing principles and mandatory intent, with standards beneath it converting that intent into specific, testable requirements such as formats, thresholds, or retention periods. Standards are what auditors and engineers can check objectively, so they form the bridge between principle and operational control.

Question 27Data Governance and Strategy

In a governance operating model, which body typically holds decision rights over cross-domain data issues such as conflicting definitions and enterprise-wide prioritization?

  1. The help desk
  2. The data engineering team
  3. The data governance council Correct answer.
  4. The internal audit function

Explanation

A governance council or equivalent cross-functional body is chartered to arbitrate issues that exceed a single domain's authority, including conflicting definitions and enterprise prioritization. Operational teams execute, audit assures, and support functions serve users, but none of them holds enterprise decision rights over data.

Question 28Data Governance and Strategy

Which role is accountable for the fitness for purpose of data within a defined business domain and for approving its use in new contexts?

  1. The data consumer
  2. The records clerk
  3. The data owner Correct answer.
  4. The platform administrator

Explanation

The data owner is the accountable role for a domain's data: quality, permitted uses, and approvals for new consumption. This accountability is a business responsibility, which is why it is assigned to a domain leader rather than to technical or administrative staff.

Question 29Data Governance and Strategy

Which practice gives a data governance program its clearest mandate and durable funding in a large enterprise?

  1. A volunteer community of interested analysts
  2. A tooling purchase led by the IT department
  3. A one-off awareness campaign at launch
  4. Executive sponsorship with defined decision rights and reporting lines Correct answer.

Explanation

Durable governance depends on sanctioned authority: an executive sponsor plus explicit decision rights and reporting lines makes the program able to enforce decisions and defend its budget. Without that mandate, governance activity tends to stall when priorities shift.

Question 30Data Governance and Strategy

A data governance team wants each critical data element to have a named accountable person, a documented definition, and a defined quality threshold. Which artifact should hold these three attributes together?

  1. A vendor risk register
  2. A change advisory calendar
  3. A network topology diagram
  4. A business glossary entry linked to a quality rule Correct answer.

Explanation

A glossary entry captures the definition and accountable owner, and linking it to a quality rule attaches the measurable threshold. Keeping all three attributes on one governed record makes accountability, meaning, and verification traceable together.

Question 31Data Governance and Strategy

A governance lead must choose between enforcing a single enterprise-wide definition of 'active customer' and allowing each region to define it locally. Which criterion should drive the decision?

  1. Whether each region has its own analytics tool
  2. Whether the definition feeds regulatory or financial reporting that requires consistency Correct answer.
  3. Whether the local definitions were documented earlier
  4. Whether regional teams prefer their existing local wording

Explanation

The decisive test is the consequence of inconsistency: where a definition drives regulatory or financial reporting, divergence creates misstatement and audit risk, so enterprise consistency wins. Local preference, documentation history, and tooling are not valid grounds for permitting divergent regulated metrics.

Question 32Data Governance and Strategy

An organization classifies datasets by sensitivity and wants handling controls to follow automatically. Which design choice makes the classification scheme most effective for that purpose?

  1. Leave handling rules to each team's discretion
  2. Tie each level to explicit, testable handling rules for storage, access, and sharing Correct answer.
  3. Classify only data that resides in the warehouse
  4. Use a long list of overlapping labels so teams can pick the closest fit

Explanation

Classification only drives controls when each level maps to concrete, verifiable rules covering storage, access, and sharing. Overlapping labels and discretionary interpretation produce inconsistent handling, and excluding data outside the warehouse leaves major repositories ungoverned.

Question 33Data Governance and Strategy

A governance council must decide how much authority to delegate to domain-level stewardship teams. Which delegation model best balances speed with enterprise consistency?

  1. The council approves every individual data change request
  2. Delegation is deferred until all domains reach equal maturity
  3. Domains operate with full autonomy and inform the council afterwards
  4. Domains decide within published enterprise guardrails and escalate exceptions to the council Correct answer.

Explanation

Federated delegation works when domains act inside published guardrails and route genuine exceptions upward, which preserves both speed and consistency. Full autonomy sacrifices consistency, central approval of every change destroys speed, and waiting for uniform maturity stalls progress indefinitely.

Question 34Data Governance and Strategy

A data governance function is asked to prove that its controls are operating as designed rather than merely documented. Which evidence set is most direct?

  1. The number of glossary terms created
  2. The published policy library and its version history
  3. Sampled control execution records, exception logs, and remediation closure dates Correct answer.
  4. The governance org chart and meeting minutes

Explanation

Operating effectiveness is demonstrated by evidence that controls actually ran: samples of executions, logged exceptions, and proof that remediation closed. Policy libraries, org charts, and term counts show design and activity volume, not whether controls functioned.

Question 35Data Governance and Strategy

A business unit wants to use a customer dataset for a purpose not covered when the data was originally collected. Which governance step should occur before the new use begins?

  1. Proceed and document the new purpose in the next quarterly review
  2. Copy the data into a sandbox so the original purpose record stays unchanged
  3. Anonymize the dataset after the analysis is complete
  4. Assess whether the new purpose is compatible and obtain any required approvals or consents Correct answer.

Explanation

Purpose limitation requires that a new use be assessed for compatibility with the original basis and approved, with fresh consent obtained where needed, before processing starts. Retrospective documentation, sandbox copying, or later anonymization does not cure processing that was unauthorized at the time.

Question 36Data Governance and Strategy

Two units report different revenue figures: one compliant with statutory accounting rules and one adjusted for management analysis. How should governance treat these definitions?

  1. Let each unit publish its figure without labels
  2. Force both units to adopt the statutory definition for all reporting
  3. Maintain both as separately named, governed metrics with documented purposes and reconciliation Correct answer.
  4. Merge them into a single blended metric

Explanation

Legitimate differences in purpose justify separate governed metrics, provided each is distinctly named, documented, and reconciled so consumers understand the gap. Forcing one definition breaks management analysis, unlabeled figures cause confusion, and blending destroys the meaning of both.

Question 37Data Governance and Strategy

A multinational faces a local legal requirement to erase certain records while a global policy mandates long retention. What is the most defensible governance resolution?

  1. Follow the global policy everywhere to keep a single rule
  2. Follow the local law silently without documenting the deviation
  3. Apply a documented jurisdiction-specific exception with legal sign-off and record the rationale Correct answer.
  4. Suspend both requirements until the conflict is resolved

Explanation

Conflicting mandatory requirements are handled through a documented, legally approved exception that records the reasoning and scope, preserving both compliance and auditability. Silent deviation hides risk, blanket global application breaches local law, and suspending both leaves the organization non-compliant on two fronts.

Question 38Data Governance and Strategy

A governance program reports high training completion and many published policies but cannot show that data quality improved or that decisions got faster. Which measurement gap does this reveal?

  1. Too few policies have been published
  2. Activity metrics are being reported in place of outcome metrics Correct answer.
  3. Training was delivered to the wrong audience
  4. The program lacks an executive sponsor

Explanation

Training counts and policy volumes are activity measures that show effort, not results. A value case requires outcome measures tied to business performance, such as defect rates, decision cycle time, or cost of remediation, which this reporting set omits.

Question 39Data Governance and Strategy

A regulator asks how the organization ensures that a sensitive dataset's approved use stays within its authorized scope over time. Which control design answers this most directly?

  1. A one-time approval signed at project kickoff
  2. An annual awareness email to analysts
  3. Periodic recertification of access and use against the approved purpose, with automatic revocation on lapse Correct answer.
  4. A data catalog entry describing the dataset

Explanation

Scope drift is controlled by recurring recertification that re-tests actual use against the approved purpose and removes access when it lapses. One-time approvals decay, awareness emails do not verify use, and a catalog description documents the dataset without enforcing scope.

Question 40Data Governance and Strategy

An organization wants governance to enable domain-published data products without recreating a central bottleneck. Which arrangement best fits that goal?

  1. Enterprise-defined interoperability standards and discoverability requirements, with domains accountable for product quality Correct answer.
  2. Domains publishing freely with no shared contract conventions
  3. A single central team building all data products
  4. Central approval of every data product before publication

Explanation

Data-product operating models scale when the center sets the rules of the road, such as interoperability standards and discoverability, while domains own quality and delivery. Central approval of each product or central building recreates the bottleneck, and free publication without conventions prevents reliable consumption.

Question 41Data Architecture and Modeling

In a dimensional model, which schema places dimension tables in third normal form while keeping the fact table free of redundant descriptive attributes?

  1. Wide denormalized table
  2. Snowflake schema Correct answer.
  3. Data vault
  4. Star schema

Explanation

A snowflake schema normalizes dimension tables into multiple related tables, reducing redundancy but adding joins. The fact table still holds only keys and measures, so it stays free of descriptive attributes. A star schema keeps dimensions denormalized in single tables instead.

Question 42Data Architecture and Modeling

A team needs a table that stores one row per business event with foreign keys to dimensions and numeric measures. Which construct are they building?

  1. A bridge table
  2. A dimension table
  3. A satellite table
  4. A fact table Correct answer.

Explanation

Fact tables capture measurable business events at a defined grain, holding dimension foreign keys plus additive numeric measures. Dimension tables hold descriptive context, bridge tables resolve many-to-many relationships, and satellites hold descriptive history in data vault.

Question 43Data Architecture and Modeling

Which property must a column satisfy to be safely summed across every dimension in a fact table?

  1. Cardinality
  2. Selectivity
  3. Additivity Correct answer.
  4. Granularity

Explanation

An additive measure can be summed across all dimensions without distortion, such as quantity sold. Semi-additive measures like balances cannot be summed across time. Cardinality, selectivity and granularity describe other characteristics and do not govern safe summation.

Question 44Data Architecture and Modeling

What does the grain of a fact table declare?

  1. The exact business meaning of one row Correct answer.
  2. The storage format used on disk
  3. The refresh frequency of the load
  4. The number of dimensions joined to it

Explanation

Grain states precisely what a single fact row represents, such as one order line per day. Declaring grain first prevents mixing levels of detail and double counting. Storage format and refresh cadence are physical or operational choices unrelated to grain.

Question 45Data Architecture and Modeling

Which key is generated by the warehouse and carries no business meaning, insulating the model from source system changes?

  1. Composite key
  2. Surrogate key Correct answer.
  3. Natural key
  4. Foreign key

Explanation

A surrogate key is a system-generated identifier assigned by the warehouse, so it stays stable even when source business keys change. Natural keys come from source systems and can be reused or reformatted. Composite keys combine multiple columns, and foreign keys simply reference another table's key.

Question 46Data Architecture and Modeling

Which modeling approach organizes data into hubs, links and satellites to support auditable, source-agnostic integration?

  1. Data vault Correct answer.
  2. Object-relational mapping
  3. Snowflake schema
  4. Star schema

Explanation

Data vault modeling separates business keys into hubs, relationships into links, and descriptive attributes with history into satellites. This structure supports parallel loading and full auditability across sources. Star and snowflake schemas target analytical query performance rather than integration auditability.

Question 47Data Architecture and Modeling

Which notation depicts entities as rectangles, relationships as lines, and cardinality with crow's foot symbols?

  1. UML class diagram
  2. Crow's foot ER notation Correct answer.
  3. Bachman notation
  4. Chen notation

Explanation

Crow's foot notation uses rectangles for entities and lines whose ends show one or many cardinality with fork-like symbols. Chen notation uses diamonds for relationships, and Bachman uses arrowheads. UML class diagrams model software classes rather than relational entities specifically.

Question 48Data Architecture and Modeling

Which normal form eliminates transitive dependencies of non-key attributes on the primary key?

  1. Third normal form Correct answer.
  2. Fourth normal form
  3. Second normal form
  4. First normal form

Explanation

Third normal form requires that no non-key attribute depend transitively on the primary key through another non-key attribute. First normal form addresses atomic values, second normal form removes partial dependencies, and fourth normal form addresses multivalued dependencies.

Question 49Data Architecture and Modeling

A retail warehouse stores one row per order line and also stores the order-level shipping charge on every line. Analysts summing shipping charges across lines overstate revenue. Which design issue is present?

  1. The measure is stored at a finer grain than its true grain Correct answer.
  2. The fact table lacks a degenerate dimension
  3. The schema is in fourth normal form
  4. The dimension is missing a surrogate key

Explanation

Shipping charge applies once per order but is repeated on each order line, so summing it multiplies the value. The measure belongs at order grain in a separate fact table or must be allocated deliberately. Surrogate keys and degenerate dimensions do not cause this overcounting.

Question 50Data Architecture and Modeling

An insurance model must show the policy attributes as they were when each claim occurred, even after the policy is updated. Which technique satisfies this requirement?

  1. A slowly changing dimension of type 2 Correct answer.
  2. A degenerate dimension
  3. A junk dimension
  4. A slowly changing dimension of type 1

Explanation

Type 2 slowly changing dimensions preserve history by inserting a new row with new version keys and validity dates whenever attributes change. Type 1 overwrites history, and junk and degenerate dimensions do not track attribute change over time.