A Review on Data Quality Dimensions for Big Data

Big Data wave has led to a rapid increase in the amount of data being collected by organizations. While the accuracy and reliability of prediction models are often prioritized, the quality of the collected data is frequently overlooked. Poor data quality can result in the common problem of ‘garbage...

Full description

Saved in:
Bibliographic Details
Published in:Procedia computer science 2024, Vol.234, p.341-348
Main Authors: Ridzuan, Fakhitah, Zainon, Wan Mohd Nazmee Wan
Format: Article
Language:English
Subjects:
big data
data management
data quality
data quality dimension
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Big Data wave has led to a rapid increase in the amount of data being collected by organizations. While the accuracy and reliability of prediction models are often prioritized, the quality of the collected data is frequently overlooked. Poor data quality can result in the common problem of ‘garbage in, garbage out’. Traditional measures of data quality, such as accuracy, consistency, completeness, and timeliness, are no longer adequate in the era of Big Data. Therefore, this paper proposes a taxonomy of data quality dimensions specifically for Big Data, addressing emerging challenges by formulating 20 dimensions and categorizing them into four distinct categories.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2024.03.008