MDM: Master Data Management

Master data management, or MDM, is a practice that strives to ensure the uniformity, accuracy, stewardship, semantic consistency, and accountability of the organization’s data assets. Master data management is a critical process that enables transparency and is used to manage, centralize, organize, categorize, localize, synchronize and enrich master data according to business rules. In this context, master data can refer to data assets, as well as metadata about them.

The efficient management of master data in a central repository provides a single source of truth on information about data assets eliminating costly inefficiencies caused by storing data carelessly in silos. It supports business initiatives and goals employing identification, linking, and syndication of data assets.

MDM helps reduce application integration costs, improve the user experience and generate analytical information that data consumers can use in other processes. MDM offers this by overcoming several challenges.

Common Challenges in Implementing MDM

  • Data silos and multiple versions of your data with MDM
  • Different versions of data living in various repositories.
  • Better data quality
    Errors due to manual data entry.

The key to making data trustworthy and insightful is transparency, achieved through responsible practice that specifies the data’s meaning, purpose, and government policy. MDM defines and implements these policies to certify that the origin, accuracy, consistency, accessibility, security, auditability, and data ethics are under supervision according to business rules.


MDM Main Benefits

  • Focus efforts on obtaining insightful data for business.
  • Improve data accuracy, visibility, and clarity.
  • Enable secure data transparency to meet changing user needs.

While identifying master data assets is pretty straightforward, it is vital to notice that not all data fits the definition of master data. Therefore, not all data needs to be manipulated as master data. In general, master data consists of a small portion of an organization’s data assets from a volume perspective. But although it might be a small portion, it is the most complex, most valuable data to secure, maintain and manage.

Cloud Data Security with Satori

Satori, The DataSecOps platform, gives companies the ability to enforce security policies from a single location, across all databases, data warehouses and data lakes. Such security policies can be data masking, data localization, row-level security and more.

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