Design for Data Quality
Design for quality; Schema normalization
The design for data quality (DQ) is the process of designing data artifacts, such as information systems, databases, and data warehouses where data quality issues are considered relevant.
In information systems different types of data are managed; these may be structured such as relational tables in databases, semi-structured data such as XML documents, and unstructured data such as textual documents. Information manufacturing can be seen as the processing system acting on raw data of different types, whose aim is to produce information products. According to this approach, the design for data quality aims to design information-related processes (e.g., creation, updating, and delivering of information) taking into account data quality dimensions.
- 5.Jiang L, Borgida A, Topaloglou T, Mylopoulos J. Data quality by design: a goal-oriented approach. In: Proceedings of the 12th Conference on Information Quality; 2007.Google Scholar
- 7.Shankaranarayanan G, Wang RY, Ziad M. IP-MAP: representing the manufacture of an information product. In: Proceedings of the 5th Conference on Information Quality; 2000.Google Scholar
- 8.Storey V, Wang RY. Extending the ER model to represent data quality requirements. In: Wang R, Ziad M, Lee W, editors. Data quality. Boston: Kluwer; 2001.Google Scholar
- 9.Storey VC, Wang RY. Modeling quality requirements in conceptual database design. In: Proceedings of the 3rd Conference on Information Quality; 1998. p. 64–87.Google Scholar
- 10.Vassiliadis P, Bouzeghoub M, Quix C. Towards quality-oriented data warehouse usage and evolution. In: Proceedings of the 11th Conference on Advanced Information Systems Engineering; 1999. p. 164–79.Google Scholar
- 12.Wang RY, Kon HB, Madnick SE. Data quality requirements analysis and modeling. In: Proceedings of the 9th International Conference on Data Engineering; 1993. p. 670–77.Google Scholar