RESEARCH & RESOURCES

LESSON - Solving Old Problems with Enterprise Information Management

Business Objects

By Frank Dravis, Vice President of EIM Strategies, Business Objects

Have you ever heard your IT staff say, “I just need access to that data,” or, “Providing you that data would be easy, if I knew how to find it”? Helping business analysts to access and use data stored in proprietary applications can be a challenge. The application confines the capture data to that specific operation and restricts it to that environment. Take SAP, PeopleSoft, or Siebel, for example. These applications work well for their intended purposes, but what happens when you want to access and process the data in ways that aren’t supported by the vendor?

Data profiling is a case in point. Suppose a marketing department is reporting substantial duplicate contact records in its CRM system. Many of the duplicates have the same last name and phone number, but there are differences in the first names, like Bob versus Robert, or differences in the firm names, like APCC versus American Power. These variations produce duplicate contacts, which creates the need to find and analyze the domain errors in each field—data profiling and cleansing tasks.

By combining and linking the functionswithin an EIM framework, new and innovative approaches to old problems become possible. These synergiessurface only when data managerslook across the breadth of EIM.

Connecting a profiling solution to the back end of a CRM system, or any proprietary application, to analyze the underlying data can be problematic because each application has its own proprietary “business layer language.” Coding against this layer to perform near-infinite analysis tasks is a significant undertaking with one application. Supporting multiple applications is even more daunting. A profiling tool can connect directly to the back-end database of these applications because they usually use DB2, Oracle, or Microsoft SQL Server. However, the back-end physical data model usually has no easily discernible relationship to the logical user view displayed by the GUI.

This is where the synergies of functionality across an EIM (enterprise information management) framework come into play. Organizations will deploy ETL, metadata management, data federation, data quality, and other solutions found in an EIM framework to build out their IT infrastructures and allow them to connect disparate data sources to their BI, data warehouse, or CRM operations. A common practice is to build data marts from extracts of proprietary applications. Some packaged solutions allow you to quickly extract domain-specific data sets from the application and load them into a predefined data mart that matches the domain context; for example, a data mart for product data from SAP. The benefit is that these ready extracts, or “rapid marts,” require only limited knowledge of the proprietary application.

With these rapid marts, the data profiling or cleansing solution can access the data easily because the tables and columns have been exposed in a user-friendly fashion. The profiling software can even provide templates that automatically connect to the rapid mart, run a standard set of analysis tasks, and report on the findings with little user setup. Data stewards can then profile the data in the proprietary application without specialized knowledge of the back-end data model. Defect reports are easy to generate; the field mappings are provided, so IT knows what specific data fields in the application need to be cleansed. In other words, the drudgery of having to wade around in 7,000 tables of the back-end database disappears. Moreover, if the data in the rapid mart is needed for downstream operations, it can be cleansed at that point without affecting the application.

By combining and linking the functions within an EIM framework, new and innovative approaches to old problems become possible. These synergies surface only when data managers look across the breadth of EIM and consider unique ways of supporting one capability with another.

This article originally appeared in the issue of .

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