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Information Strategy:
Building a Data Management Strategy Part 2: Technology

  Column published in DM Review Magazine
November 2005 Issue
  By Jane Griffin

In last month's column, I began an in-depth series about master data management (MDM) in a service-oriented architecture (SOA). That column focused on the process component of the MDM framework that must be built to implement an SOA. This column continues that discussion and focuses on the technology necessary to support the MDM framework.

The technology behind the MDM framework consists of an explicit, layered path for data to move through the framework. First is the data integration layer that retrieves data from all applicable IT systems. This layer consists of messaging, synchronization, cross-referencing, mapping and process management tools. Here, data from organizational IT systems is cleansed, transformed, loaded and routed to the next layer: the data management layer.

The data management layer houses correct data definitions and the master data model for the company's information architecture. Thus, it is the main source of "truth" about organizational data. This layer also serves as the framework's data consolidation engine. The cleansed, transformed data from the data integration layer is cataloged and aggregated here and awaits distribution to the portal or data presentation layer.

The data presentation layer usually takes the form of an enterprise portal that disseminates information based on user roles and security levels. However, from an MDM perspective, the most important part of the presentation layer is transparent to the user. It is an MDM server that facilitates change management across business performance management (BPM) and transaction systems.

While the layered MDM framework appears straightforward in its construction, if it is built well, it actually consists of highly sophisticated, market-leading data integration, management and presentation tools that coalesce into a powerful, smoothly functioning unit. It is incredibly important to select the right tools - in the right combination - to ensure that what you want is actually what you end up with.

Let's start with the tools that make up the data integration layer. These tools are also known as data quality (DQ) and data extraction, transformation and loading (ETL) tools. They should be specifically designed to function in an SOA environment. There are myriad DQ and ETL toolsets on the market; however, it is only in the past several years that vendors have designed tools to fit in SOA environments.

ETL and DQ tools for SOAs allow administrators to design data integration services that developers can use without necessarily understanding all the complexities of all the data sources or individual technologies. These services can also easily be shared by relevant applications or processes. Finally, SOA-specific ETL and DQ tools also enable higher levels of reuse for the SOA's data integration logic rules.

The data management toolset should also be selected with the SOA environment in mind; but in an MDM context, it is not so much about the SOA environment as it is about facilitating enterprise-wide MDM consolidation. Obviously, the data management toolset should enable management and exchange of master data - standard and nonstandard - on key subjects such as products, customers, brands, market segments and geographies. It should also permit flexible master data modeling that can be used across all applications. Finally, it should enhance enterprise data governance by enabling business people to manage master data quality via collaboration and workflow management technologies.

As I said earlier, the data presentation layer in an MDM framework focuses on enabling enhanced, seamless change management across business performance management (BPM) and transaction systems. To do this, the data presentation toolset must include an MDM server that allows the organization to handle (and correct) differences in data elements, merge fields when necessary, perform data import/exports easily, and establish and monitor audit trails. It must also be highly scalable. Further, it must integrate with other IT systems to support an enterprise deployment model with support for enterprise ERP, CRM, legacy, customized and packaged systems. From an SOA perspective, the data presentation tools you choose should make the loosely coupled nature of the SOA transparent to users, in that it should present a cohesive interface, no matter what services are requested.

When you are implementing an MDM framework in preparation for or in conjunction with an SOA, often success will be at least partially measured as a function of which tools you choose. It is crucial that you choose tools with top-quality functionality and scalability. It is also essential that you choose tools that have been designed to fit in the loosely coupled, service-based SOA environment. Working closely with your vendor partners should ensure that you choose the right tools for your company. After that, implementation will present challenges, but the finished product should be well worth the effort! 


For more information on related topics visit the following related portals...
Data Quality, Enterprise Information Management, ETL, Master Data Management and Reference Data.

Jane Griffin is a Deloitte Consulting partner. Griffin has designed and built business intelligence solutions and data warehouses for clients in numerous industries. She may be reached via e-mail at janegriffin@deloitte.com

Deloitte Consulting LLP Principals Lee Dittmar and Jane Griffin talk about the importance of closing the gap between data and information in a podcast entitled "Compliance and IT: A Catalyst for Change."

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