MDM stands for Master Data Management.Master Data of an organization drives the Transactions .So Master Data quality directly influences the reporting quality.That is why Master Data Management has become such a prominent domain of expertise.
Organizational challenges are the “people” challenges – the ones that are introduced as a by-product of changing the way people both manage and view information. There are 4 issues to be taken care of broadly.
• The Strategic Vision
• Data Ownership
• Performance-Oriented Management
• Change Management
Operational Challenges
Choosing to deploy a master data management program is a strategic decision that reverberates across the enterprise.
Just like the operational challenges of construction projects are finessed through proper planning and governance, the critical operational challenges of MDM involve instituting the appropriate oversight into a rapidly changing environment, including:
• Data Quality Management
• Data Standards Management
• Data Governance
• Data Integration
Technology Challenges
Master data management is not just software; it is a solution that embodies a management program, linking technology, principles, and policies. Once the governance infrastructures are in place, and the policies have been defined and endorsed within the enterprise, though, there are a number of technical hurdles that must also be cleared for a smooth migration to the MDM environment:
• Selecting and MDM Architecture style
• Transitioning to the new infrastructure
• Performance
The IT scenario consists of the following scenario variants:
�� Master-data consolidation
Allows to identify identical master data objects within heterogeneous landscapes,
merge identical objects centrally, and provide the relevant key mapping information for
further use in business operations or analytics.
�� Master-data harmonizationOrganizations can cleanse master data on materials, retail articles, suppliers, and
customers and leverage the results to perform enterprise-wide analytics, such as
global spend analyses. Consolidated master data is then distributed to the connected
remote systems to streamline business operations based on high-quality data.
�� Central master-data managementOrganizations can consolidate and centrally manage their master data. They can
support company-wide quality standards by ensuring that central control of master
data begins as soon as the data is created.
The concepts embodied by a service oriented architecture (SOA) are often conveyed in the same breath as a master data management solution. And since a services-based approach can incorporate the way we address a number of these challenges, it is reasonable to consider SOA as part of your strategic vision, mostly as a way of integrating MDM within a governance framework.
For example, an assessment of the application architecture may reveal that similar approaches are employed by a number of different applications for the creation of a new customer record. In this case, a “master record creation” service can be configured to accommodate each of those applications requirements, which will both simplify future application development and ease the transition process. Applying this across all application requirements can both support a migration plan for applications as well as support the behavioral transition plan as part of change management.
In fact, because SOA can support the execution of the policies described within the data governance framework, the services-oriented approach can contribute to addressing most of the challenges described in this paper. Data ownership, performance management, data quality and data standards, data integration and the transition strategy can benefit from the identification and configuration of enterprise-wide set of services. By addressing these issues in a strategic manner, one can have high confidence in executing a successful MDM program.
Bluesky
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