What is Master Data Management and How it Aids Data Governance?

CIO Review Europe | Friday, December 03, 2021

The application of master data management concepts helps in the development of data management strategies.

FREMONT, CA: Even though data is acknowledged mainly as driving the digital workplace, there is an issue. Enterprise data is stored in various silos, making it nearly impossible to obtain a single perspective of the truth. While this presents enormous issues for sales and customer management, the consequences for data governance and compliance are generally disregarded.

Over the years, various initiatives have been made to address this issue, one of the most significant of which is master data management (MDM). MDM is a technology-enabled business discipline that ensures the uniformity, stewardship, governance, accuracy, semantic consistency, and accountability of an enterprise's official shared master data assets. The following are some of the things that an MDM platform should offer:

  • Through reconciliation, support the worldwide identification, linkage, and synchronization of master data across diverse data sources.
  • Create and manage a central, persistent master data system or index of the record.
  • To support various business objectives, enable the development and delivery of a trustworthy version of one or more data domains to all stakeholders.
  • Workflow-based monitoring and corrective-action strategies can help with ongoing master data stewardship and governance requirements.

MDM is a technology-enabled business discipline in which IT and business collaborate to ensure the uniformity, accuracy, stewardship, governance, semantic consistency, and accountability of an organization's official shared master data assets.

The application of MDM concepts aids in the development of data management strategies. MDM creates a multi-disciplinary approach because it is a broad-spectrum technique. To strengthen accountability, people might be allocated responsibility for specific data (data stewards and owners). Data managers must establish rules for how data is acquired and where it is necessary to categorize similar data collections. Managers also have access to several solutions that automate data management. These systems can track record sources, organize data, and standardize data sets using intelligent artificial intelligence. These technologies are beneficial and vital for large businesses, but MDM can be maintained without them.

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