Data Quality Management Flashcards
6 cards from real CDP practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 Data Quality Management flashcards as text
What does 'data deduplication' specifically address?
Answer: Identifying and removing or merging duplicate records representing the same real-world entity
Data deduplication identifies records that represent the same entity (e.g., the same customer) and removes or merges them to create a single, accurate record.
What is 'referential integrity' in relational databases?
Answer: A constraint ensuring that foreign key values in a child table match existing primary key values in the parent table
Referential integrity ensures that every foreign key value in a child table corresponds to an existing primary key value in the parent table, preventing orphaned records.
Which technique uses statistical analysis to identify records that deviate significantly from expected patterns, indicating potential quality issues?
Answer: Outlier Detection / Anomaly Analysis
Outlier and anomaly detection uses statistical methods to identify data values or records that fall outside expected ranges, signaling potential quality issues.
What is 'data standardization' in data quality management?
Answer: Converting data to a common format, structure, or value set to ensure consistency
Data standardization converts data to consistent formats, structures, and representations (e.g., date formats, address formats, abbreviation expansion) to enable accurate comparison and integration.
What is the cost of poor data quality most directly associated with in business terms?
Answer: Flawed business decisions, wasted effort on rework, and lost revenue opportunities
Poor data quality leads to flawed business decisions, costly rework, regulatory fines, lost customers, and missed revenue opportunities.
Which data quality practice involves monitoring data quality metrics continuously and alerting stakeholders when thresholds are breached?
Answer: Data Quality Monitoring / Alerting
Data quality monitoring continuously tracks quality metrics against defined thresholds and triggers alerts when data quality degrades below acceptable levels.
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