Data Quality Issues in Big Data: A Review

Data with good quality has precedence when analyzing and using big data to deduce value from such tremendous volume of data in today's business environments. Decisions and insights derived from poor data has a negative and unpredictable consequences to organizations. At present, due to the lack of comprehensive and intensive research in the field of data quality, especially large data, there is an urgent need to address this issue by researchers to reach the optimal way to estimate and evaluate the quality of large data. Thus, enabling institutions to make rational decisions based on evaluation outputs. In this paper, the current research on the quality of large data was reviewed and summarized by exploring the basic characteristics of large data. The main challenges facing the quality of information were also discussed in the context of large data. Some of the initiatives suggested by the researchers to evaluate the quality of the data have been highlighted. Finally, we believe that the results of these reviews will enhance the conceptual measurements of the large data quality and produce a concrete groundwork for the future by creating an integrated data quality assessment and evaluation models using the suitable algorithms.