Data Quality Management Flashcards

Which metric expresses the proportion of records that pass all applicable data quality rules?

Answer: Data quality score (DQ score)

A DQ score (often expressed as a percentage) is calculated as the ratio of conforming records to total records across one or more quality dimensions.

A healthcare organization must ensure that patient records are accurate, complete, and available within 30 minutes of a clinical event. Which framework element formally defines these requirements?

Answer: Data quality service level agreement (DQ SLA)

A Data Quality SLA formally specifies measurable quality targets (accuracy, completeness, latency) and the consequences of non-compliance for a given dataset.

What distinguishes 'reactive' data quality management from 'proactive' data quality management?

Answer: Reactive DQ fixes defects after they occur; proactive DQ prevents defects from arising

Reactive DQ detects and corrects defects post-hoc, while proactive DQ redesigns processes, controls, and entry points to prevent defects from entering the data ecosystem.

Which data quality concept refers to the degree to which data correctly represents the real-world construct it is intended to model?

Answer: Accuracy

Accuracy is the dimension that measures how faithfully data values reflect the true state of the real-world objects or events they represent.

During a data migration project, what is the primary purpose of running data quality checks BEFORE migration begins?

Answer: To establish a baseline and prevent inheriting existing defects in the target system

Pre-migration DQ checks establish a baseline of existing defects and allow remediation before those defects are replicated and potentially amplified in the new target environment.

A company's address data was loaded using abbreviations ('St' vs 'Street', 'Blvd' vs 'Boulevard'). What type of data quality issue is this?

Answer: Consistency / standardization issue

Inconsistent representation of the same concept (abbreviated vs. spelled-out street suffixes) is a consistency or standardization issue that hinders matching and aggregation.

Which practice ensures that data quality rules remain aligned with evolving business requirements over time?

Answer: Continuous rule review cycles tied to business process change management

Embedding DQ rule reviews into the change management process ensures rules are updated whenever business processes, regulations, or data sources change.