CDS Data Quality Management 3

Question 1

Which of the following best describes 'data profiling' in a data quality context?

Accepted Answer

Analyzing data to understand its structure, content, and quality characteristics

Answer

Encrypting sensitive fields before storage

Answer

Defining business rules for acceptable data values

Answer

Publishing data to a data marketplace

Question 2

When implementing a 'right-first-time' data quality strategy, what is the primary focus?

Accepted Answer

Preventing defects at the point of data entry or creation

Answer

Retroactively cleansing historical data in bulk

Answer

Automating downstream error correction after ingestion

Answer

Archiving low-quality records for future remediation

Question 3

A data quality rule flags all ZIP codes that do not match the U.S. five-digit or ZIP+4 format. This is an example of which type of rule?

Accepted Answer

Format/pattern rule

Answer

Referential integrity rule

Answer

Cross-field consistency rule

Answer

Threshold rule

Question 4

What is the COST OF POOR DATA QUALITY (CPDQ) model primarily used for?

Accepted Answer

Quantifying the financial impact of data defects to justify DQ investments

Answer

Estimating storage costs for duplicate records

Answer

Benchmarking data quality against industry peers

Answer

Calculating the number of FTE hours spent on manual data entry

Question 5

Which data quality technique involves comparing data against a trusted external reference source to verify accuracy?

Accepted Answer

Data reconciliation with a golden record

Answer

Data normalization

Answer

Data benchmarking

Answer

Data certification

Question 6

In a data quality framework, what distinguishes a 'critical data element' (CDE) from a regular data element?

Accepted Answer

CDEs have a disproportionate impact on business outcomes if they are incorrect

Answer

CDEs are stored only in relational databases

Answer

CDEs are always encrypted at rest

Answer

CDEs are never modified after initial entry

Question 7

Which of the following is a key output of a Data Quality Assessment (DQA)?

Accepted Answer

A prioritized inventory of data quality issues with business impact ratings

Answer

A fully cleansed production dataset ready for use

Answer

A new data model that eliminates all quality problems

Answer

An automated ETL pipeline configured to reject bad data