Resolving data duplication, inaccuracy and inconsistency issues using Master Data Management

Abstract

The management of scattered datasets over multiple data sources has led to data quality issues in an organization. Master Data Management (MDM) has been used to resolve this issue by providing “a single reference of truth” to reduce data redundancy in an organization. To the best of our knowledge, there is lack of study reviewing the progress of MDM research. Therefore, this paper intends to fill in the gap by conducting a systematic literature review to summarize the progress of MDM research domain. We also synthesize the data quality issues on multiple data sources management and how MDM tends to resolve them. We strategized our literature methods through relevant keywords searching from nine (9) databases including journals, proceedings, books, book chapters and industry research. The strategy has shown seven hundred and seventy-seven (777) articles were found during the initial searching stage and three hundred and forty-seven (347) relevant articles were filtered out for the analysis. The review shows that currently, MDM research has received a slope of enlightenment hence it still relevant to be explored. MDM is not just about a technology, it is an approach through a combination of processes, data governance, and technical implementation to resolve data quality issues on multiple data sources management such as duplication, inaccuracy and inconsistency of information.