Synonyms
Design for quality; Schema normalization
Definition
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.
In the database field, the design for data quality has the objective of producing good (with respect to a given set of quality dimensions) conceptual and relational schemas and...
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Recommended Reading
Batini C, Scannapieco M. Data quality: concepts, methodologies and techniques. New York: Springer; 2006.
Dayal U. Query processing in a multidatabase system. In: Kim W, Reiner DS, Batory DS, editors. Query processing in database systems. New York: Springer; 1985. p. 81–108.
Jarke M, Jeusfeld MA, Quix C, Vassiliadis P. Architecture and quality in data warehouses: an extended repository approach. Inf Syst. 1999;24(3):229–53.
Jeusfeld MA, Quix C, Jarke M. Design and analysis of quality information for data warehouses. In: Proceedings of the 17th International Conference on Conceptual Modeling; 1998. p. 349–62.
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.
Navathe SB. Evolution of data modeling for databases. Commun ACM. 1992;35(9):112–23.
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.
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.
Storey VC, Wang RY. Modeling quality requirements in conceptual database design. In: Proceedings of the 3rd Conference on Information Quality; 1998. p. 64–87.
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.
Wang RY. A product perspective on total data quality management. Commun ACM. 1998;41(2):58–65.
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.
Wang RY, Reddy MP, Kon HB. Toward quality data: an attribute-based approach. Decis Support Syst. 1995;13(3–4):349–72.
Wang RY, Storey VC, Firth CP. A framework for analysis of data quality research. IEEE Trans Knowl Data Eng. 1995;7(4):623–40.
Wang RY, Ziad M, Lee YW. Data quality. Boston: Kluwer; 2001.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC, part of Springer Nature
About this entry
Cite this entry
Batini, C., Maurino, A. (2018). Design for Data Quality. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_649
Download citation
DOI: https://doi.org/10.1007/978-1-4614-8265-9_649
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-8266-6
Online ISBN: 978-1-4614-8265-9
eBook Packages: Computer ScienceReference Module Computer Science and Engineering