Developing master data services templates

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Over the past few posts we've looked at developing an integration strategy to enable the rapid alignment of candidate business processes with the services provided by a master data environment. As part of a preparatory step, it is valuable to at the very least understand the implementation requirements to meet the business needs. The next level of preparation would be to have design templates for the each of the necessary services associated with the underlying system components to ensure the levels of service and performance can be met.

For example, presume an online process that needs to perform an identity search each time a customer attempts to create a new account. The performance criteria are defined in terms of data volume (how much data needs to be shared for the identity searches), simultaneous load (how many search requests at the same time) and response time (how fast must the system provide an answer). Having templates for implementation that can be tuned to meet the desired performance will speed integration with the MDM environment.

You can anticipate those implementation details by evaluating the potential development needs, designing the templates for implementation and even implementing the various services on platforms that can meet a reasonable combination of requirements. Provide a matrix that maps each of the master data service usage scenarios to the desired performance characteristics. An example is shown in table 1.

Table 1: Mapping master data services

In each cell of the matrix, specify the performance requirements for the different levels of performance. Master data service templates can then be designed so as to meet those performance needs. The selection of a deployment platform can be based on reasonable expectations for combinations of levels of service and the ability to satisfy the performance criteria.

Anticipating the types of services required and their corresponding performance needs provides a means of evaluating the suitability of different techniques, algorithms and methods of implementation. Developing templates for implementation based on these anticipated needs helps to more rapidly integrate with candidate business processes.

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About Author

David Loshin

President, Knowledge Integrity, Inc.

David Loshin, president of Knowledge Integrity, Inc., is a recognized thought leader and expert consultant in the areas of data quality, master data management and business intelligence. David is a prolific author regarding data management best practices, via the expert channel at b-eye-network.com and numerous books, white papers, and web seminars on a variety of data management best practices. His book, Business Intelligence: The Savvy Manager’s Guide (June 2003) has been hailed as a resource allowing readers to “gain an understanding of business intelligence, business management disciplines, data warehousing and how all of the pieces work together.” His book, Master Data Management, has been endorsed by data management industry leaders, and his valuable MDM insights can be reviewed at mdmbook.com . David is also the author of The Practitioner’s Guide to Data Quality Improvement. He can be reached at loshin@knowledge-integrity.com.

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