- Referential integrity in a relational database ensures that:
Answer: A foreign key value in one table must match an existing primary key value in the related table, preventing orphaned records.
Referential integrity enforces valid relationships between tables - a record in a child table must reference an existing record in the parent table, preventing broken links (orphaned records). Answer D is correct. Encryption (A) is a security control. Duplicate prevention (B) is uniqueness/entity integrity. Backup (C) is a recovery control.
- An organization implements a validation rule that prevents users from entering a birth date that is later than today's date in the HR system. This is an example of which type of data quality control?
Answer: Input validation - a range or logic check that prevents invalid data from being entered.
A validation rule that prevents future birth dates is an input validation control - specifically a logic/range check that enforces data accuracy at the point of entry. Answer A is correct. Output controls (B) are detective, not preventive. Encryption (C) is a security measure. Normalization (D) is a database design concept.
- An organization implements automated edit checks that prevent users from saving a sales order unless all required fields (customer ID, product code, quantity, price) are completed. This type of control addresses which data quality dimension?
Answer: Completeness - ensuring all required data elements are present before a record is saved.
Required field validation prevents records from being saved with missing mandatory data, directly enforcing data completeness. Answer A is correct. Timeliness (B) relates to currency of data. Consistency (C) relates to cross-system agreement. Confidentiality (D) is a security dimension, not a data quality dimension.
- An organization's accounts receivable system contains multiple customer records for the same customer with slightly different name spellings. This data quality issue is best described as a:
Answer: Duplicate record or data consistency problem reducing data accuracy and reliability.
Multiple records for the same entity with inconsistent data is a duplicate/consistency problem - a classic data quality issue that can cause errors in reporting and customer communications. Answer C is correct. Referential integrity (A) concerns foreign key relationships, not duplicates. Confidentiality (B) is unrelated. Normalization (D) addresses redundancy in schema design, not record-level duplicates.
- A company uses a data quality scorecard to measure and monitor the quality of data across key systems. Which of the following is the primary benefit of this approach?
Answer: It provides ongoing visibility into data quality trends, enabling proactive identification and remediation of quality issues before they affect business processes.
A data quality scorecard provides continuous measurement and trending of quality metrics, enabling organizations to detect deteriorating data quality early and take corrective action. Answer A is correct. Scorecards supplement, not replace, internal audit (B). Automatic correction does not result from scorecards alone (C). Human oversight by data stewards remains necessary (D).
- Which of the following is the primary risk of poor data quality in an organization's financial reporting systems?
Answer: Materially misstated financial statements resulting from inaccurate, incomplete, or inconsistent data.
Poor data quality in financial systems directly risks producing inaccurate financial reports - potentially leading to material misstatements, regulatory violations, and loss of stakeholder confidence. Answer D is correct. Network latency (A), storage costs (B), and employee morale (C) are secondary or operational concerns, not the primary risk.
- A batch processing system processes 10,000 payroll transactions. As a data integrity control, which of the following should be verified after processing?
Answer: That the record count and total payroll amount after processing match the pre-processing control totals.
Comparing post-processing record counts and financial totals to pre-processing control totals verifies that all transactions were processed completely and accurately - a run-to-run control total check. Answer C is correct. Encryption verification (A) addresses security. Individual review (B) is impractical for 10,000 records. Access logging (D) does not verify processing accuracy.
- A data migration project moves customer records from a legacy system to a new CRM platform. Which of the following is the most critical data quality control to implement during migration?
Answer: Reconciling record counts and key data fields between the source and target systems to verify the migration was complete and accurate.
Data migration reconciliation - comparing record counts, totals, and key field values between the source and target - is the most critical control to verify that all records were migrated completely and without corruption. Answer D is correct. Encryption (A), training (B), and immediate archiving (C) are important but do not directly verify migration integrity.
- A company imports customer data from an external source into its CRM system. Before loading the data, the company should perform which of the following data quality procedures?
Answer: Validate, cleanse, and reconcile the imported data to ensure it meets quality standards before loading into the production system.
Before loading external data into a production system, organizations should validate format and completeness, cleanse errors, and reconcile record counts and totals to prevent introducing poor-quality data. Answer C is correct. Granting immediate access (A) bypasses data review. Encryption without validation (B) doesn't address quality. Archiving without review (D) defeats the purpose of the import.
- Which of the following represents a data completeness control in an accounts receivable system?
Answer: Generating alerts when customer invoices do not have a corresponding payment or aging update within a defined period.
Alerting on invoices without payment or aging updates identifies potentially missing or incomplete transaction records - a completeness control ensuring all expected follow-on activity is captured. Answer D is correct. Encryption (A) is a confidentiality control. Access restriction (B) is an authorization control. Supervisor approval (C) is an authorization control.
- An organization's data governance framework assigns 'data stewards' to each major data domain. The primary responsibility of a data steward is to:
Answer: Define and enforce data quality standards, resolve data issues, and manage the accuracy and consistency of data within their assigned domain.
A data steward is accountable for the quality, consistency, and fitness for use of data in their domain - defining standards, resolving issues, and coordinating with data owners and users. Answer A is correct. Encryption (B), backup (C), and schema development (D) are IT operational or technical functions, not data stewardship roles.
- Which of the following is an example of a 'master data management' (MDM) control?
Answer: Establishing a single authoritative source (golden record) for customer data that all systems reference to ensure consistency.
MDM creates a single, trusted version of key business data (customers, products, vendors) that all systems reference, eliminating inconsistencies that arise from maintaining duplicate master records in multiple systems. Answer A is correct. Encryption (B), backup (C), and access restriction (D) are important controls but do not define MDM.
- Which of the following best describes 'data profiling' as a data quality assessment technique?
Answer: Analyzing a dataset's structure, content, and statistics (null rates, value distributions, format compliance) to assess its quality before processing.
Data profiling examines the characteristics of a dataset - completeness, format consistency, value ranges, null rates - to identify quality issues before the data is used in analytics or processing. Answer C is correct. Encryption (A), user personas (B), and data lineage (D) are unrelated to data profiling.
- An organization's financial system allows journal entries to be posted without a corresponding debit and credit balance (i.e., unbalanced entries are accepted). This represents a failure of which data integrity control?
Answer: Processing controls - the system should reject or flag entries that do not balance before they are posted.
Accepting unbalanced journal entries is a processing control failure - the system should validate that debits equal credits before accepting any journal entry, a fundamental accounting data integrity rule. Answer B is correct. Referential integrity (A) concerns table relationships. Encryption (C) is a security control. Access controls (D) address authorization.
- An organization discovers that its data warehouse contains records with null values in the 'customer segment' field, which is used to generate management reports. The most appropriate corrective action is to:
Answer: Investigate the root cause of the missing values, remediate the data, and implement validation controls to prevent future occurrences.
The correct approach is to investigate why the values are missing (system error, process failure, data migration issue), fix the existing data, and implement controls to prevent recurrence. Answer D is correct. Deleting records (A) loses valid transaction data. Blanket replacement (B) masks the problem without fixing it. Encryption (C) does not address data completeness.
- A company reconciles the total number of records and sum of amounts in its daily sales interface file against the corresponding entries in the general ledger. This procedure primarily addresses which data quality concern?
Answer: Data completeness and accuracy - verifying that all sales transactions were transferred completely and correctly between systems.
Reconciling record counts and amounts between systems verifies that all transactions were completely and accurately transferred - addressing completeness (no missing records) and accuracy (correct amounts). Answer C is correct. Confidentiality (A) and security (B) are not addressed by reconciliation. Normalization (D) is a schema design concept.
- Which of the following data quality issues would most likely cause errors in a company's financial consolidation process?
Answer: Inconsistent account coding and chart of accounts structures across subsidiaries, making it impossible to accurately aggregate financial data.
Inconsistent chart of accounts and account coding across subsidiaries is a major data consistency problem that directly prevents accurate financial consolidation - transactions may be miscategorized or unmappable. Answer B is correct. Font sizes (A) are formatting issues. Time zones (C) and decimal display (D) are manageable technical issues that do not inherently prevent consolidation.
- An IT auditor reviews the data entry controls for a payroll system and finds that the system accepts salary amounts of zero dollars for active employees without generating an alert. This represents a failure of which type of control?
Answer: Input validation control - the system should reject or flag implausible values such as zero salary for active employees.
Accepting zero salary for active employees without an alert is a failure of input validation - a reasonableness or logic check that should flag implausible entries. Answer D is correct. Output controls (A) detect errors after processing. Access controls (B) restrict who can enter data. Encryption (C) protects data confidentiality.
- Which of the following data integrity controls helps ensure that a batch of transactions is complete and has not been lost or added during processing?
Answer: Record counts and control totals that are compared before and after processing.
Record counts and hash/control totals established before processing are compared to post-processing results to verify that all records were processed correctly and none were added or lost. Answer B is correct. Data masking (A) protects confidentiality. Access controls (C) restrict authorization. Encryption (D) protects data in transit.
- Which of the following data quality controls would be most effective at detecting records that have been entered multiple times in an accounts payable system?
Answer: Automated duplicate detection routines that compare key fields (vendor ID, invoice number, amount, date) and flag matches.
Automated duplicate detection analyzes key transaction fields to identify records that appear to be duplicates, directly addressing the risk of duplicate payments. Answer B is correct. Encryption (A), training (C), and access restriction (D) do not detect existing duplicate records.
