In this digital transformation era, data is growing exponentially due to substantial online transactions and the internet of things, etc. As data is growing, it needs efficient data management and scalable storage mechanisms to deal with the vast data that is generated.

Now plenty of tools, technologies, and frameworks are available that can handle this kind of Big Data scenario with distributed systems that can scale horizontally on the cloud platforms. Master Data Management (MDM) is a technology-enabled discipline in which the information technologies team works closely with business teams to ensure data accountability to achieve uniformity, accuracy, consistency, a single source of truth, etc.

Current MDM systems cannot address quality-related issues such as reliable, real-time data synchronization, deduplication, entity resolution, etc. , due to multi-folded data growth.

The following four major gaps from the above quality barriers can be drawn as gaps in the research and have been addressed in this book. • Unclear master data definition• Lack of responsibilities in data maintenance• Inaccurate data matching• Immature data deduplication process.

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