Database Systems Practice Test 2026 - Free Database Practice Questions and Study Guide

This item is about data quality in terms of whether every required data element is actually present. The degree to which all required data is present in a collection is called completeness. If essential fields are missing—like a customer record lacking an address or an order missing a price—the completeness drops because the dataset doesn’t have all the necessary information. Completeness can be measured by the share of records that have all required attributes or by the availability of non-null values across those fields. This is different from consistency (data agreeing across datasets or rules), timeliness (data being up-to-date), and conformity (data following defined formats or standards), which is why completeness is the best fit for describing whether all required data is present.