I85PREP
⌘ K
DABCC study materials
DABCC study resources

DABCC practice questions

One question at a time. Build your DABCC understanding.

First 50 of 200 questions. Each one lists the choices, the correct answer, and an explanation. The checker at the top of this page saves progress in this browser when it is available.

Continue in the practice tool above to load more questions, 50 at a time.

Question 1Data Governance and Stewardship

In a data governance operating model, what is the primary distinction between a data owner and a data steward?

  1. The owner is an external auditor, while the steward is an internal auditor responsible for control testing.
  2. The owner writes SQL transformations, while the steward approves the production deployment of those transformations.
  3. The owner is accountable for a data domain and its decisions, while the steward executes day-to-day quality and policy activities on the owner's behalf. Correct answer.
  4. The owner maintains the technical metadata catalog, while the steward defines the enterprise data strategy.

Explanation

Accountability and execution are separated in a governance operating model: the data owner is the accountable decision-maker for a domain, and the steward performs the operational work of defining rules, monitoring quality, and resolving issues. This separation lets decisions escalate to a single accountable role while daily work stays close to the data.

Question 2Data Governance and Stewardship

A governance council is deciding who may approve a new customer data domain. Which artifact most directly establishes that authority?

  1. A decision rights matrix (RACI) covering domain ownership and approval Correct answer.
  2. A data quality dashboard showing current defect counts
  3. A glossary entry defining the term customer
  4. A backup and restore runbook for the customer database

Explanation

Decision rights documentation such as a RACI matrix assigns who is responsible, accountable, consulted, and informed for each governance decision, which is exactly what an approval question requires. Dashboards, glossaries, and runbooks support governance but do not confer authority.

Question 3Data Governance and Stewardship

Which statement best describes the purpose of a business glossary within a data governance program?

  1. It provides agreed business definitions so that terms mean the same thing across systems and reports. Correct answer.
  2. It enforces referential integrity constraints in the operational database.
  3. It stores row-level access logs for regulatory reporting.
  4. It replaces the need for a data catalog by holding physical schema details.

Explanation

A business glossary captures approved definitions, synonyms, and ownership of business terms so that reporting and analytics use consistent meaning. It is a semantic artifact, not an access log, physical schema repository, or database constraint mechanism.

Question 4Data Governance and Stewardship

A data steward finds that the 'customer_lifetime_value' field is populated by three different calculations across two reporting marts. Which governance action addresses the root cause rather than the symptom?

  1. Increase the refresh frequency of both reporting marts.
  2. Add a footnote to each report explaining that values may differ.
  3. Assign a single approved calculation as the governed metric definition and require marts to conform to it. Correct answer.
  4. Suppress the field from all reports until the next fiscal year.

Explanation

Conflicting calculations are a definition problem, so the durable fix is to agree one governed metric definition, record it with ownership in the glossary or metrics layer, and require downstream consumers to conform. Suppression, footnotes, and faster refreshes leave the inconsistency in place.

Question 5Data Governance and Stewardship

An organization wants to classify data so that handling rules can be applied consistently. Which approach best supports that goal?

  1. Classify only data stored in the cloud warehouse.
  2. Classify data once at project kickoff and never revisit the classification.
  3. Define an enterprise classification scheme with defined levels, criteria, and required handling controls per level. Correct answer.
  4. Let each team invent its own labels and handling rules.

Explanation

A classification scheme works when levels, assignment criteria, and the handling controls required at each level are defined centrally and applied consistently. Local label schemes, partial coverage, and one-time classification all undermine consistent handling.

Question 6Data Governance and Stewardship

A regulator asks the firm to demonstrate that personal data in a marketing dataset is used only for approved purposes. Which governance mechanism most directly provides that evidence?

  1. A capacity plan for the marketing analytics cluster
  2. A recorded purpose limitation and consent mapping tied to the dataset and reviewed periodically Correct answer.
  3. An incident log of past database outages
  4. A code review checklist for SQL formatting standards

Explanation

Purpose limitation evidence comes from documenting the approved purposes and the consent or legal basis for each data element, then reviewing that mapping as usage changes. Capacity plans, formatting standards, and outage logs do not connect data use to approved purposes.

Question 7Data Governance and Stewardship

What is the core purpose of a data retention schedule in a governance program?

  1. To define the encryption algorithm used for data at rest
  2. To guarantee that all data is kept indefinitely for future analytics
  3. To specify how long each data category is kept and when it must be disposed of, based on legal and business requirements Correct answer.
  4. To list the names of employees who may query a dataset

Explanation

A retention schedule maps each data category to a retention period and a disposal trigger derived from legal, regulatory, and business needs. It is distinct from encryption standards and access authorization lists, and it never implies indefinite retention.

Question 8Data Governance and Stewardship

A data quality issue is traced to missing mandatory values in a supplier master feed. Which governance response is most appropriate first?

  1. Delete the affected supplier records to clean the table.
  2. Record the issue, assign an owner, and agree a data quality rule with the source system team. Correct answer.
  3. Immediately block all procurement transactions company-wide.
  4. Publish the raw feed to all analysts for transparency.

Explanation

Governance handles quality defects through a defined issue-management path: log the issue, assign accountability, and establish a measurable rule with the source owner so the defect is prevented upstream. Blocking everything, deleting records, or broadly publishing bad data creates new risk.

Question 9Data Governance and Stewardship

Which pair correctly matches a metadata type with its example?

  1. Business metadata: database index fragmentation percentage
  2. Technical metadata: approved definition of 'active customer'
  3. Business metadata: column data type and maximum length
  4. Operational metadata: job run timestamp and row count processed Correct answer.

Explanation

Operational metadata describes runtime facts such as job execution timestamps, row counts, and error logs. Business metadata covers definitions and ownership, while technical metadata covers structures such as data types and lengths.

Question 10Data Governance and Stewardship

A governance team needs to prove that a critical report's figures can be trusted. Which combination of controls provides the strongest evidence?

  1. A screenshot of the report stored in a shared drive
  2. A weekly meeting where stakeholders discuss report popularity
  3. An email from the report developer confirming the numbers look right
  4. Documented lineage from source to report plus reconciled control totals and a certified, owned metric definition Correct answer.

Explanation

Trust evidence combines traceability of the data path, reconciliation to independent control totals, and a certified definition with a named owner. Screenshots, informal assurances, and popularity discussions do not demonstrate accuracy or traceability.

Question 11Data Governance and Stewardship

What distinguishes a data domain from a data product in a modern data governance model?

  1. A domain is a backup site, while a product is a disaster recovery plan.
  2. A domain is a bounded business area with an accountable owner, while a product is a governed, documented output that the domain publishes for consumers. Correct answer.
  3. A domain is a vendor contract, while a product is a software license.
  4. A domain is a technical storage layer, while a product is a query language.

Explanation

A data domain groups data by business area under a single accountable owner, and a data product is the packaged, documented, quality-assured output that domain publishes with clear contracts for consumers. The other pairings confuse governance concepts with infrastructure or legal artifacts.

Question 12Data Governance and Stewardship

A firm adopts a policy that requires stewardship review before any new field containing personal data goes live. Which governance lever is being used?

  1. A compensating control replacing encryption
  2. A corrective control applied during disaster recovery
  3. A preventive control embedded in the change process Correct answer.
  4. A detective control applied after an incident

Explanation

Requiring review before go-live is a preventive control because it stops noncompliant changes before they reach production. Detective controls find problems after the fact, corrective controls remediate after an event, and compensating controls substitute for an unavailable control.

Question 13Data Governance and Stewardship

Which activity is the clearest example of stewardship rather than ownership?

  1. Serving as the final escalation point for cross-domain disputes
  2. Approving the enterprise data strategy budget
  3. Accepting residual risk for a customer data domain
  4. Curating glossary terms and resolving definition conflicts for a domain Correct answer.

Explanation

Stewardship is hands-on curation and coordination, such as maintaining glossary terms and resolving definition conflicts. Budget approval, risk acceptance, and final escalation are accountability decisions that sit with owners or governance councils.

Question 14Data Governance and Stewardship

A data sharing agreement with a third party is being drafted. Which governance element is most important to specify in addition to permitted use?

  1. The internal code review process of the receiving party
  2. The preferred meeting cadence for joint reviews
  3. The brand colors used in the partner's dashboards
  4. The retention and deletion obligations, including return or destruction at termination Correct answer.

Explanation

Sharing agreements must define what happens to data at the end of the arrangement, including retention limits and return or destruction obligations, alongside permitted use. Presentation details, internal engineering processes, and meeting schedules are not core data protection terms.

Question 15Data Governance and Stewardship

What is the main governance risk of allowing business units to maintain separate, unlinked glossaries?

  1. Reduced ability to encrypt data at rest
  2. Slower network throughput between regions
  3. Increased storage costs in the warehouse
  4. Loss of consistent meaning across reports, causing conflicting decisions from the same data Correct answer.

Explanation

Unlinked glossaries let the same term carry different meanings, so reports and decisions diverge even when the underlying data is identical. Storage, network, and encryption concerns are technical matters unrelated to semantic fragmentation.

Question 16Data Governance and Stewardship

A steward must decide whether a newly requested attribute is in scope for the customer domain. Which criterion is most defensible?

  1. Whether the attribute describes a customer entity and falls within the domain's agreed boundary and owner approval Correct answer.
  2. Whether the requesting team has budget for the change
  3. Whether the attribute was requested during a sprint planning meeting
  4. Whether the attribute name is under twenty characters

Explanation

Domain scope is determined by whether the data describes the domain's core entity and by the agreed boundary and owner approval, not by budget, naming length, or timing of the request. This keeps boundaries stable and auditable.

Question 17Data Governance and Stewardship

Which statement correctly describes a data classification level of 'restricted' compared with 'internal'?

  1. Internal data requires stricter controls than restricted data.
  2. Restricted data may be freely shared externally because it is already protected by law.
  3. Both levels require identical handling because classification only affects storage cost.
  4. Restricted data requires stronger access controls and handling safeguards because unauthorized disclosure causes greater harm. Correct answer.

Explanation

Higher classification levels reflect greater potential harm from disclosure and therefore demand stronger access, encryption, and sharing controls. Classification drives handling requirements; it never authorizes free external sharing and does not leave levels equivalent.

Question 18Data Governance and Stewardship

A governance program wants to measure whether stewardship is effective. Which metric is most meaningful?

  1. Total count of meetings held by the governance council
  2. Number of emails sent to the data office
  3. Percentage of critical data elements with an assigned owner, certified definition, and passing quality rules Correct answer.
  4. Number of glossary terms created regardless of usage

Explanation

Effectiveness metrics tie stewardship to outcomes: coverage of critical data elements by ownership, certified definitions, and quality rules that pass. Raw counts of terms, meetings, or emails measure activity rather than results.

Question 19Data Governance and Stewardship

Which scenario best illustrates a conflict of interest that governance should address through segregation of duties?

  1. A steward defines a quality rule and a developer implements it in a pipeline
  2. An analyst requests a new dashboard and a steward prioritizes it
  3. A data owner sponsors a domain and a steward maintains its glossary
  4. The same individual both approves access to sensitive data and performs the periodic access review Correct answer.

Explanation

Segregation of duties separates authorization from verification so that one person cannot grant access and then confirm it was appropriate. The other pairings describe normal collaboration between complementary roles without self-approval risk.

Question 20Data Governance and Stewardship

What is the primary role of a data governance council?

  1. Writing production ETL code for each domain
  2. Managing the procurement of laptop hardware
  3. Performing daily database backups
  4. Setting policy, resolving cross-domain conflicts, and overseeing adherence to governance standards Correct answer.

Explanation

A governance council is a decision-making body that sets policy, arbitrates cross-domain issues, and monitors compliance with standards. It does not perform engineering, backup operations, or hardware procurement.

Question 21Data Governance and Stewardship

A new regulation requires that data subjects can obtain a copy of their personal data. Which governance capability is most directly needed to respond within the required timeframe?

  1. A new vendor contract for office supplies
  2. A larger analytics cluster for faster queries
  3. A revised brand style guide
  4. A documented inventory linking personal data elements to systems and owners so requests can be located and fulfilled Correct answer.

Explanation

Fulfilling access requests depends on knowing where personal data lives and who owns it, which requires an inventory or data map with ownership. Compute capacity, branding, and procurement do not enable locating and assembling subject data.

Question 22Data Governance and Stewardship

Which statement about data ownership in a federated governance model is accurate?

  1. Ownership is eliminated because stewardship replaces it.
  2. Ownership is delegated to business domains that follow centrally defined standards and report adherence. Correct answer.
  3. Ownership is centralized in the IT department for all domains.
  4. Ownership applies only to unstructured data.

Explanation

Federated governance delegates ownership to business domains while a central function defines standards and monitors adherence. It neither centralizes all ownership in IT nor removes ownership, and it applies across structured and unstructured data.

Question 23Data Governance and Stewardship

A steward discovers that a critical data element has no documented definition and three teams use it differently. Which sequence best reflects sound governance practice?

  1. Delete the element from all systems
  2. Publish all three definitions and let consumers choose
  3. Escalate immediately to the regulator without internal review
  4. Convene the stakeholders, agree one definition with an owner, record it, and communicate the change Correct answer.

Explanation

Sound practice resolves definitional conflict through stakeholder agreement, records the approved definition with ownership, and communicates it to consumers. Publishing conflicting definitions, deleting data, or escalating externally before internal resolution are not appropriate first steps.

Question 24Data Governance and Stewardship

Which artifact primarily records the approved handling requirements for each classification level?

  1. A project charter for the analytics team
  2. A data classification policy with a handling control matrix Correct answer.
  3. A service level agreement for network uptime
  4. A glossary of financial acronyms

Explanation

A classification policy paired with a handling control matrix states what controls apply at each level, such as encryption, access approval, and sharing restrictions. Project charters, uptime SLAs, and acronym lists do not define handling requirements.

Question 25Data Governance and Stewardship

A team proposes storing production personal data in a personal cloud account to speed up analysis. Which governance response is most appropriate?

  1. Ignore it because the data is already internal
  2. Approve it because it accelerates delivery
  3. Approve it only if the account has a strong password
  4. Reject it and direct the team to an approved environment with the required controls and access review Correct answer.

Explanation

Storing personal data outside approved environments bypasses access control, monitoring, and retention safeguards, so governance should reject the practice and route the work to an approved environment. A strong password alone does not supply the missing organizational controls.

Question 26Data Governance and Stewardship

In a data governance operating model, which body is typically accountable for resolving cross-domain conflicts over data definitions and for ratifying enterprise-wide data policies?

  1. The IT service desk, which handles user access requests
  2. The data stewards assigned to each individual domain
  3. The internal audit function, which independently tests control design
  4. The data governance council, composed of senior representatives from business and technology Correct answer.

Explanation

A governance council exists to make enterprise-level decisions that no single domain can make alone, including ratifying policy and arbitrating cross-domain disputes over definitions and priorities. Audit provides independent assurance rather than decision authority, stewards execute within domains, and the service desk handles operational requests.

Question 27Data Governance and Stewardship

A firm wants a single authoritative list of approved business terms, each with a definition, owner, and linked physical assets. Which governance artifact should it establish?

  1. A disaster recovery runbook for the reporting platform
  2. A business glossary integrated with the metadata repository Correct answer.
  3. A data retention schedule covering all systems
  4. An entity-relationship diagram of the core warehouse

Explanation

A business glossary holds approved terms and definitions, and linking it to the metadata repository ties each term to the physical assets that implement it, giving one authoritative vocabulary. The other artifacts describe structure, retention, or recovery and do not govern terminology.

Question 28Data Governance and Stewardship

A steward is asked to certify a critical data element for regulatory reporting. Which evidence most directly supports certification that the element is fit for that use?

  1. A count of how many users accessed the element in the last quarter
  2. Documented definition, named owner, validated quality rules with passing results, and a traceable lineage to the report Correct answer.
  3. An approval email from the vendor that supplied the source system
  4. A backup schedule confirming the element is copied nightly

Explanation

Certification means the element is defined, owned, and demonstrably controlled, so the steward needs the definition, accountability, measured quality against agreed rules, and lineage showing how the value reaches the report. Usage counts, vendor emails, and backup schedules say nothing about fitness for regulatory reporting.

Question 29Data Governance and Stewardship

Two business units both claim authority to approve changes to a shared customer identifier used across products. Which governance mechanism most appropriately resolves this before the conflict delays delivery?

  1. Let each unit maintain its own version of the identifier and reconcile differences downstream
  2. Assign a single accountable owner for the element and route disputed changes to the governance council for escalation Correct answer.
  3. Suspend all changes to the identifier until the units reach an informal agreement
  4. Delegate the decision to the vendor that supplies the source system

Explanation

Shared critical elements need one accountable owner plus a defined escalation path, so disputes are settled by decision rights rather than by informal negotiation. Duplicating the identifier, freezing change indefinitely, or outsourcing the decision all leave accountability unclear and risk divergence.

Question 30Data Governance and Stewardship

A governance lead reviews why stewardship engagement is low in one region. Stewards there are named in a register but have no time allocation, no decision rights over the data they oversee, and no visibility of issues raised elsewhere. Which diagnosis best explains the failure?

  1. The governance policy was approved at too senior a level for the region
  2. The roles were established as nominal appointments without authority, capacity, or an operating rhythm to act on issues Correct answer.
  3. The stewards were recruited from business teams rather than from central IT
  4. The region lacks sufficient technical tooling to profile data quality automatically

Explanation

Stewardship fails when accountability is declared but not enabled: without allocated time, defined decision rights, and a routine for surfacing and tracking issues, named stewards cannot influence outcomes. Tooling, reporting line, and the seniority of policy approval are secondary factors that do not by themselves explain the absence of action.

Question 31Data Architecture and Modeling

In a dimensional model, which term describes a fact table whose grain is one row per individual transaction line, with no pre-aggregation applied?

  1. Transaction fact table Correct answer.
  2. Aggregate fact table
  3. Periodic snapshot fact table
  4. Accumulating snapshot fact table

Explanation

A transaction fact table stores one row per atomic business event at the declared grain, preserving full detail. Snapshot variants store periodic states or lifecycle milestones, and aggregate tables store pre-computed summaries rather than the atomic events.

Question 32Data Architecture and Modeling

A dimension table contains a row for each product version with EffectiveDate and EndDate columns, and the fact table stores the surrogate key of the version valid at event time. Which technique is this?

  1. Slowly changing dimension Type 2 Correct answer.
  2. Type 1 overwrite
  3. Degenerate dimension
  4. Junk dimension

Explanation

Type 2 slow changing dimensions preserve history by inserting a new versioned row with validity dates and assigning a new surrogate key. Facts then reference the version that was current when the event occurred, enabling point-in-time reporting.

Question 33Data Architecture and Modeling

Which modeling approach stores all attributes as key-value pairs with valid-from and valid-to timestamps, allowing full history without schema changes for new attributes?

  1. Star schema
  2. Third normal form
  3. Data vault Correct answer.
  4. Snowflake schema

Explanation

Data vault models business keys in hubs, relationships in links, and descriptive context in satellite tables that carry load timestamps and optional end dates. This structure preserves full history and absorbs new attributes without altering existing structures.

Question 34Data Architecture and Modeling

In relational modeling, a foreign key constraint on an order line table referencing the order header primarily enforces which property?

  1. Referential integrity Correct answer.
  2. User-defined integrity
  3. Entity integrity
  4. Domain integrity

Explanation

Referential integrity guarantees that every non-null foreign key value matches an existing primary key in the referenced table. This prevents orphaned child rows such as order lines without a parent order.

Question 35Data Architecture and Modeling

A team is designing a conceptual data model for a new claims system and must agree on business entities and relationships before any physical design. Which artifact level are they producing?

  1. Canonical message model
  2. Logical data model
  3. Physical data model
  4. Conceptual data model Correct answer.

Explanation

A conceptual model captures business entities, relationships, and high-level rules independent of technology. Logical models add attributes and keys, and physical models add platform-specific details such as indexes and data types.

Question 36Data Architecture and Modeling

Which characteristic best distinguishes a data lakehouse architecture from a traditional data warehouse?

  1. It stores only structured relational tables in a proprietary format.
  2. It eliminates the need for any metadata catalog.
  3. It combines open file storage with transactional table management and schema enforcement. Correct answer.
  4. It requires all data to be loaded through ETL before landing.

Explanation

A lakehouse layers ACID transactional table formats and schema governance over low-cost open file storage. This lets the same storage serve both raw data and curated analytical tables.

Question 37Data Architecture and Modeling

An analyst needs to report sales by month and by region from a star schema. Which design element most directly supports fast slicing by region?

  1. A bridge table between product and sales
  2. A surrogate key on the sales fact table
  3. A region dimension key referenced by the sales fact table Correct answer.
  4. A degenerate dimension holding the invoice number

Explanation

A conformed region dimension joined through a foreign key in the fact table allows grouping and filtering by region attributes. The fact table carries the region key so queries can slice measures by region without scanning unrelated structures.

Question 38Data Architecture and Modeling

Which metadata component in a data catalog describes the meaning, allowed values, and ownership of a data element?

  1. Lineage metadata
  2. Business metadata Correct answer.
  3. Operational metadata
  4. Technical metadata

Explanation

Business metadata documents definitions, allowed values, business rules, and data ownership in business terms. Technical metadata covers structures and types, operational metadata covers run statistics, and lineage covers data flow.

Question 39Data Architecture and Modeling

A retail chain wants a single customer dimension usable by sales, service, and marketing marts. Which design concept is required?

  1. A mini-dimension
  2. A role-playing dimension
  3. A conformed dimension Correct answer.
  4. A snowflaked dimension

Explanation

A conformed dimension is a shared, identically defined dimension used across multiple fact tables and marts. It guarantees that measures from different processes can be compared and combined consistently.

Question 40Data Architecture and Modeling

A fact table must track a loan application moving through submission, approval, and disbursement. Each row should be updated as milestones occur, with dates for each milestone. Which fact table type fits?

  1. Accumulating snapshot fact table Correct answer.
  2. Transaction fact table
  3. Periodic snapshot fact table
  4. Factless fact table

Explanation

An accumulating snapshot holds one row per process instance and updates milestone dates and lag measures as the workflow progresses. This directly supports cycle-time analysis across the application lifecycle.

Question 41Data Architecture and Modeling

A dimension changes frequently in a few volatile attributes, causing Type 2 history to grow rapidly. Which technique reduces this growth while retaining history?

  1. Outrigger dimension
  2. Role-playing dimension
  3. Junk dimension
  4. Mini-dimension Correct answer.

Explanation

A mini-dimension extracts the fast-changing attributes into a compact dimension with its own surrogate key referenced by the fact table. This avoids creating a new full dimension row each time a volatile attribute changes.

Question 42Data Architecture and Modeling

A data vault model has a hub for customer, a link between customer and address, and a satellite on the customer hub. Where should a customer's changing credit rating be stored?

  1. In the customer hub as an attribute
  2. In a satellite attached to the customer hub Correct answer.
  3. In a separate hub keyed by credit rating
  4. In the customer link as a descriptor

Explanation

Satellites hold descriptive attributes and their history, attached to a hub or link by the parent key. A changing credit rating therefore belongs in a satellite on the customer hub with load timestamps.

Question 43Data Architecture and Modeling

A query joins a fact table to a date dimension four times to filter by order date, ship date, delivery date, and return date. Which dimension design is being used?

  1. Role-playing dimension Correct answer.
  2. Bridge dimension
  3. Degenerate dimension
  4. Conformed dimension

Explanation

A single date dimension referenced multiple times with different meanings is a role-playing dimension. Each reference uses a distinct foreign key and a distinct view or alias with its own role name.

Question 44Data Architecture and Modeling

A team is choosing between normalization and denormalization for an analytical mart. Which trade-off is most accurate?

  1. Normalization reduces join complexity for analysts; denormalization increases storage redundancy.
  2. Denormalization always improves write throughput for transactional systems.
  3. Both approaches eliminate redundancy equally but differ only in naming conventions.
  4. Denormalization reduces join complexity for analysts; normalization reduces update anomalies and redundancy. Correct answer.

Explanation

Denormalized star schemas reduce the number of joins and simplify analytical queries. Normalized models reduce redundancy and update anomalies but require more joins, which suits transactional workloads.

Question 45Data Architecture and Modeling

A sales fact table must capture discounts that apply at the order level while other measures apply at the line level. What is the correct modeling response?

  1. Split into two fact tables, one at order grain and one at line grain Correct answer.
  2. Add the discount to the product dimension
  3. Remove the discount measure from the model
  4. Store order-level discounts on every line to keep a single grain

Explanation

All measures in a fact table must share the same grain, so mixing order-level and line-level measures would double-count. Separate fact tables at order grain and line grain, each linked to conformed dimensions, preserve correctness.

Question 46Data Architecture and Modeling

Which statement correctly describes the relationship between a business key and a surrogate key in a dimension table?

  1. The surrogate key is warehouse-generated and stable; the business key comes from the source and may change. Correct answer.
  2. The business key is generated by the warehouse; the surrogate key comes from the source system.
  3. The surrogate key must be a natural composite of all dimension attributes.
  4. Both keys must be identical to simplify joins.

Explanation

Surrogate keys are meaningless integers generated within the warehouse, providing stability and compact joins. Business keys originate in source systems and can be reused or reformatted, so they are not reliable join keys.

Question 47Data Architecture and Modeling

A modeler needs to represent a many-to-many relationship between patients and diagnoses in a dimensional schema while preserving weighting. Which structure is appropriate?

  1. A degenerate dimension in the fact table
  2. A Type 3 dimension with a previous-value column
  3. A bridge table between the fact and the dimension Correct answer.
  4. A junk dimension

Explanation

A bridge table sits between the fact table and a dimension to resolve many-to-many relationships, optionally carrying weight factors for allocation. This preserves correct aggregation when multiple dimension values attach to one event.

Question 48Data Architecture and Modeling

An architect must document which source columns feed each target column and which transformations apply. Which metadata capability delivers this requirement?

  1. Schema versioning
  2. Column-level lineage Correct answer.
  3. Data profiling statistics
  4. Data quality scorecards

Explanation

Column-level lineage maps each target column back to its source columns and the transformations applied along the path. This supports impact analysis when a source column changes.

Question 49Data Architecture and Modeling

A factless fact table is most appropriate for which requirement?

  1. Capturing the current credit limit of each customer
  2. Recording the total revenue for each sales transaction
  3. Tracking which products were on promotion in each store on each day, regardless of sales Correct answer.
  4. Storing monthly inventory balances by warehouse

Explanation

A factless fact table records the occurrence of events or coverage relationships without numeric measures. Promotion coverage by product, store, and day is a classic case where presence of a row itself carries meaning.

Question 50Data Architecture and Modeling

A data model must enforce that every account belongs to exactly one customer, while a customer may own many accounts. Which cardinality notation expresses this correctly?

  1. One-to-many from customer to account, with mandatory participation on the account side Correct answer.
  2. Many-to-one from customer to account, with optional participation on the account side
  3. One-to-one between customer and account
  4. Many-to-many between customer and account

Explanation

The rule states that one customer relates to many accounts, and each account must relate to exactly one customer. That is a one-to-many relationship with mandatory participation on the account side.