Introduction to Data Quality

What is the definition of data quality?

• A perception of data's fitness for purpose in a specific context

• Data that has been archived

• Data stored in a secure system

• Data that has no errors

Which data quality dimension assesses whether the data accurately reflects real-world entities?

• Timeliness

• Completeness

• Consistency

• Accuracy

Data is considered consistent if:

• It has a unique format

• It aligns across the entire enterprise

• It contains no null values

• It includes metadata

Which of the following refers to "data about data"?

• Accuracy

• Metadata

• Completeness

• Timeliness

Timeliness in data quality refers to:

• Data being complete

• Data being delivered to the right person at the right time

• Data being unique

• Data being free of errors

What does data completeness measure?

• Whether data is accurate

• The degree to which data is fully provided

• Whether data is delivered on time

• The security of the data

Which of these is NOT a conventional data quality dimension?

• Accuracy

• Security

• Uniqueness

• Timeliness

Data integrity ensures that:

• Data is protected from deliberate manipulation

• Data is updated frequently

• Data is stored in multiple formats

• Data is unique

What is a common problem in data quality?

• Having too much metadata

• Duplicated, inconsistent, and incomplete data

• Data being accessible only to administrators

• Data being archived

Which is an example of a data quality metric?

• Metadata description

• Schema conformance

• Backup configuration

• Database size