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In a recent podcast, ebizQ's Peter Schooff spoke with Jignesh Shah, vice president of business infrastructure products and solutions at Software AG. They discussed Software AG's purchase of the master data management (MDM) company Data Foundations, focusing on its implications for BPM and SOA. What follows is a transcript of their conversation, edited for editorial style, clarity and length.

PS: Can you give me the thinking behind Software AG's purchase of Data Foundations?



JS: Sure. Software AG acquired Data Foundations so that we could help our customers improve business performance through master data management. To give you a bit more background, Software AG is focused on helping both the CIO and the business managers use technology--particularly BPM, SOA and integration--to improve and adapt business processes. What we have found was that business processes are frequently broken due to poor quality of information about products, customers, suppliers and so on. Core information is spread throughout different applications and tends to be rife with redundancies, inaccuracies and incompleteness.

As a result, this poor data quality frequently leads to highly inefficient processes, poor operational decisions and, sometimes, outright failures in everything from fulfilling orders to providing customer service to meeting compliance requirements. So it became clear to us that organizations need a single and reliable view of business critical data as a foundation for process improvement and for creating flexible IT capabilities. This is why we acquired Data Foundations, which is a well-regarded master data management vendor. Now MDM is a strategic extension of our BPM and SOA solutions.

PS: Why have customers recently been focusing on eliminating master data quality issues at the source?

JS: Traditionally, MDM has focused on cleaning up and organizing master data like customer end products for reporting and analytics purposes. This is often referred to as "analytical MDM." In this approach, you are primarily worried about cleaning up data in data warehouses [and other locations] that are downstream from operational systems. Unfortunately, this approach does not address the root causes of why the data is inconsistent to begin with, because it's broken in the operational systems.

Meanwhile, businesses are under ever-increasing pressure to improve efficiency and performance of operational processes-for example, providing customer service that spans multiple products and lines of business. That's a reality for most businesses today. Such pressure is shining a very harsh light on master data quality problems in the operational systems, which must be fixed in order to meet business requirements. Similarly, on the IT side, more and more IT organizations are adopting SOA.

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