Both relational and object databases can contain rather serious problems in terms of data redundancy, relationships, integrity, and structure. The objective is to design a normalized, high-fidelity database while minimizing complexity. When evaluating performance there are times when de-normalization of relations may be the optimal solution. The measures used to assess the trade-offs may include query and update performance, storage, and the avoidance of data anomalies. A database that is otherwise well-designed but does not perform well is useless.
Data integrity is one of the keys to developing a quality database.
Without accurate data, users will lose confidence in the database or make uninformed decisions. The identification, interpretation, and application of business rules, however, present a more difficult challenge for the developer. Rules and policies must be communicated and translated and much of the meaning and intent can be lost in this process. Semantic quality is an important objective of database systems. Information that represents a high proportionate match between the problem and solution domains should be the goal of a database with high semantic quality.