Data Processing Data Quality and Validation

Question 1

Which data quality dimension measures whether data accurately represents the real-world entity it describes?

Accepted Answer

Accuracy

Answer

Data accuracy measures how closely stored data values reflect the true real-world values they are meant to represent.

Question 2

What is data completeness?

Accepted Answer

All required fields contain valid non-null values

Answer

Data completeness measures whether all required fields are populated with valid values, with no missing or null entries where data is expected.

Question 3

What is a data quality rule?

Accepted Answer

A defined condition that data must satisfy to be considered valid

Answer

A data quality rule specifies conditions — like 'age must be positive' or 'email must contain @' — that data must meet to be valid.

Question 4

What does data profiling involve?

Accepted Answer

Analyzing a dataset to understand its structure, content, and quality issues

Answer

Data profiling examines datasets to assess structure, distributions, null counts, and anomalies before processing or migration.

Question 5

Which type of data validation checks that a value falls within an acceptable range?

Accepted Answer

Range validation

Answer

Range validation verifies that a numeric or date value falls within defined minimum and maximum bounds, e.g., age between 0 and 120.

Data Processing Practice Test