Dimensionality for Big Data Quality A review

Document Type : Original Article

Authors

1 Faculty of Computers and Artificial Intelligence, Helwan University

2 Computer science, Faculty of computers and artificial intelligence, helwan university, cairo, egypt

3 Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt

Abstract

The analysis and use of big data (BD) in today's enterprise context is dominated by high data quality (DQ). Decisions and opinions derived from poor quality data have negative and unexpected consequences for organizations. Currently, in the data quality field, researchers urgently need to consider improving the big data quality (BDQ), especially because of the lack of detailed research in this area. Considering the big data quality will allow organizations to take sensible, accurate assessment-based decisions. This article examines and summarizes current research into big data quality by discovering the fundamental qualities of big data and its quality. In big data, the main issues of data quality are also examined. The suggestions of some researchers on data quality evaluation are outlined. Examining this subject can help to improve conceptual measurements of high data quality and provide a strong basis for future researches by developing integrated analysis and evaluation of data quality models using appropriate algorithms

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