Data Quality in the Era of Big Data: A Global Review

Abstract

AbstractCurrently, Big Data is gaining wide adoption in the digital world as a new technology able to manage and support the explosive growth of data. Indeed, data is growing at a higher rate due to the variety of the data-generating adopted devices. In addition to the volume aspect, the generated data are usually unstructured, inaccurate, and incomplete, making its processing even more difficult. However, analyzing such data can provide significant benefits to businesses if the quality of data is improved. Facing the fact that value could only be extracted from high data quality, companies using data in their business management focus more on the quality aspect of the gathered data. Therefore, Big data quality has received a lot of interest from the literature. Indeed, many researchers have attempted to address Big data quality issues by suggesting novel approaches to assess and improve Big data quality. All these researches inspire us to review the most relevant findings and outcomes reported in this regard. Assuming that some review papers were already published for the same purpose, we believe that researchers always need an update. It is worth noting that all the published review papers are focused on a specific area of Big data quality. Therefore, this paper aims to review all the big data quality aspects discussed in the literature, including Big data characteristics, big data value chain, and big data quality dimensions and metrics. Moreover, we will discuss how the quality aspect could be employed in the different applications domains of Big data. Thus, this review paper provides a global view of the current state of the art of the various aspects of Big data quality and could be used to support future research.KeywordsBig Data QualityBig Data Quality ApproachBig Data Value ChainBig Data Quality DimensionsBig Data Characteristics