Master Data and Master Data Management

Master Data and Master Data Management

Master data
is a collection of common, core entities along with their attributes and their values that are considered critical to a company's business, and that are required for use in two or more systems or business processes. Examples of master data include customer, product, employee, supplier, and location data. Complexity arises from the fact that master data is often strewn across many channels and applications within an organization, invariably containing duplicate and conflicting data.
Master Data Management
(MDM) is the controlled process by which the master data is created and maintained as the
system of record
for the enterprise. MDM is implemented in order to ensure that the master data is validated as correct, consistent, and complete. Optionally, MDM can be implemented to ensure that Master Data is circulated in context for consumption by internal or external business processes, applications, or users.
Ultimately, MDM is deployed as part of the broader Data Governance program that involves a combination of technology, people, policy, and process. The following steps comprise the interative process of implementing an MDM solution.
Step 1: Policy
Determine who the data domain and policy makers are. The data domain and policy makers then develop policy definitions, strategies, objectives, metrics, and a revision process.
Step 2: Process
Process executers define data usage, management processes, and protocols – for people, applications, and services – including how to store, archive, and protect data.
Step 3: Controls
Process managers create controls to enforce and monitor policy compliance and to identify policy exceptions.
Step 4: Audit
Auditors review, access, and report historical performance of the system. Auditor reports then feed into governance and policy revision (step 1).
Organizations are implementing master data management solutions to enhance data reliability and data maintenance procedures. Tight controls over data imply a clear understanding of the myriad data entities that exist across the organization, data maintenance processes and best practices, and secure access to the usage of data.

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