Completeness:
Measurement accuracy:
Calculation accuracy: Are the calculation functions performing the correct calculations, and are they working as they should?
Integrity:
Individuals who know the data best are very important to successfully validate the data! Alternatively, get out on the ground and get to know the data process and content yourself!
An audit trail should always be available, i.e., how the data is collected, transformed, and stored should be documented so that it is clear at which step of the process problems may have crept in.
Data quality assurance in data warehousing
The Challenges of Data Quality and Data Quality Assessment in the Big Data Era