Welcome to the InfoSci Platform
Reference Hub7
From Data Quality to Big Data Quality

From Data Quality to Big Data Quality

Carlo Batini, Anisa Rula, Monica Scannapieco, Gianluigi Viscusi
Copyright: © 2016 |Pages: 23
ISBN13: 9781466698406|ISBN10: 1466698403|EISBN13: 9781466698413
DOI: 10.4018/978-1-4666-9840-6.ch089
Cite Chapter Cite Chapter

MLA

Batini, Carlo, et al. "From Data Quality to Big Data Quality." Big Data: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2016, pp. 1934-1956. https://doi.org/10.4018/978-1-4666-9840-6.ch089

APA

Batini, C., Rula, A., Scannapieco, M., & Viscusi, G. (2016). From Data Quality to Big Data Quality. In I. Management Association (Ed.), Big Data: Concepts, Methodologies, Tools, and Applications (pp. 1934-1956). IGI Global. https://doi.org/10.4018/978-1-4666-9840-6.ch089

Chicago

Batini, Carlo, et al. "From Data Quality to Big Data Quality." In Big Data: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 1934-1956. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-4666-9840-6.ch089

Export Reference

Mendeley
Favorite

Abstract

This chapter investigates the evolution of data quality issues from traditional structured data managed in relational databases to Big Data. In particular, the paper examines the nature of the relationship between Data Quality and several research coordinates that are relevant in Big Data, such as the variety of data types, data sources and application domains, focusing on maps, semi-structured texts, linked open data, sensor & sensor networks and official statistics. Consequently a set of structural characteristics is identified and a systematization of the a posteriori correlation between them and quality dimensions is provided. Finally, Big Data quality issues are considered in a conceptual framework suitable to map the evolution of the quality paradigm according to three core coordinates that are significant in the context of the Big Data phenomenon: the data type considered, the source of data, and the application domain. Thus, the framework allows ascertaining the relevant changes in data quality emerging with the Big Data phenomenon, through an integrative and theoretical literature review.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.