DMC Data Governance and Standards 2 — Questions and Answers
Question 1: What is the purpose of a data quality dimension in governance?
- To measure storage consumption by data domain
- To define measurable characteristics — such as completeness, accuracy, and timeliness — used to assess data quality (Correct answer)
- To segment data by geographic region
- To classify data by sensitivity level
Correct answer: To define measurable characteristics — such as completeness, accuracy, and timeliness — used to assess data quality
Data quality dimensions — including completeness, accuracy, consistency, timeliness, validity, and uniqueness — provide measurable criteria for evaluating how fit data is for its intended use.
Question 2: What is data profiling in the context of data governance and modeling?
- Creating user profiles for database access control
- Analyzing existing data to understand its structure, content, quality, and patterns (Correct answer)
- Documenting which teams access which tables
- Benchmarking query performance across tables
Correct answer: Analyzing existing data to understand its structure, content, quality, and patterns
Data profiling examines source data to discover its structure, value ranges, null rates, uniqueness, and patterns — essential input for building accurate data models and governance policies.
Question 3: What is the difference between data classification and data categorization in governance?
- They are synonymous terms used interchangeably
- Classification assigns sensitivity/security labels (PII, confidential); categorization groups data by business subject area (Finance, HR) (Correct answer)
- Classification is physical; categorization is logical
- Classification applies only to structured data; categorization to unstructured
Correct answer: Classification assigns sensitivity/security labels (PII, confidential); categorization groups data by business subject area (Finance, HR)
Data classification assigns security/sensitivity labels (public, internal, confidential, restricted) while data categorization organizes data by business domain or subject area.
Question 4: What does GDPR require of data models that store personal data of EU residents?
- All personal data must be stored unencrypted for audit purposes
- Models must accommodate data subject rights including access, correction, and erasure of personal data (Correct answer)
- Personal data columns must use numeric surrogate keys only
- All personal data must be replicated to US servers
Correct answer: Models must accommodate data subject rights including access, correction, and erasure of personal data
GDPR requires that data systems support the right to access, rectify, port, and erase personal data — data models must be designed to accommodate these rights technically.
Question 5: What is a data catalog and how does it relate to data governance?
- A list of all ETL jobs scheduled in the pipeline
- An organized inventory of data assets with metadata, definitions, and ownership that enables data discovery and governance (Correct answer)
- A read-only backup of the production database
- A list of approved SQL query templates
Correct answer: An organized inventory of data assets with metadata, definitions, and ownership that enables data discovery and governance
A data catalog provides a searchable inventory of data assets enriched with business definitions, ownership, lineage, quality metrics, and usage statistics to enable governance and self-service analytics.
Question 6: What is the purpose of a data retention policy in a data model?
- To prevent database indexes from growing too large
- To define how long data must be kept and when it should be archived or deleted based on legal and business requirements (Correct answer)
- To set limits on query execution time
- To control how many backups are stored
Correct answer: To define how long data must be kept and when it should be archived or deleted based on legal and business requirements
A data retention policy specifies the required storage duration for data categories, driving physical design decisions about archiving, partitioning, and purging strategies.
DMC Data Governance and Standards 2
What is the purpose of a data quality dimension in governance?