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What is Master Data Management?

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Master data management is the practice of implementing a single source for data. It is common for organizations to replicate data in a large number of data sources. This tends to be overly complex and leads to operational inefficiencies and risks. Master data management is about creating a standard access point for suitable data. The following are common steps in implementing master data management.

Producers & Consumers

Identifying the producers and consumers of data.


Analyzing the various data models that apply to each data entity to identify differences between sources.

Data Stewards & Custodians

Assigning data stewards and data custodians as the business and technical owners of data.

Data Governance Program

Launching a data governance council to make decisions. Data is surprisingly political and master data management requires a clear decision making structure.

Master Data Design

Design the master data. This typically includes a common data model. However, some data virtualization approaches don't bother enforcing a traditional data model.

Tool Sets

Master data management may require tools for collecting, staging, validating, transforming, normalizing, reconciliating, integrating, managing and governing data.


Implementing the single source of data and updating producers and consumers to use it and contribute to it.


The ongoing process of governing, managing and maintaining the master data.
Overview: Master Data Management
The practice of implementing a single source for data.
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Abstract Data
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Data Analysis
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Data Attribute
Data Cleansing
Data Collection
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Data Consumer
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Data Custodian
Data Degradation
Data Dredging
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Data Federation
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Structured Data
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Transactional Data
Types Of Data
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