New Names, Old Tricks? CDI, MDM, EII
I have been seeing three business terms popping up with greater frequency recently, and it is interesting to explore these ideas within a combined context. Those terms are: customer data integration (CDI), master data management (MDM) and enterprise information integration (EII).
According to Gartner, CDI is described as "the combination of the technology, processes and services needed to create and maintain an accurate, timely and complete view of the customer across multiple channels, business lines and enterprises, where there are multiple sources of customer data in multiple application systems and databases." A December 2004 report from the META Group (now part of Gartner), says "MDM is about tackling the decades-old problem of redundant and conflicting data" associated with "core information (e.g., customers, products, locations, suppliers, partners)." Lastly, according to Webopedia, EII "combines various data sources at an enterprise level in order to support applications that present or analyze the data in new ways. EII provides a service that allows administrators, developers and end users to treat a broad array of data sources as if they were one large database or data service."
While the different vendors in these corresponding spaces may dispute the details of these definitions, for the most part, each one succinctly describes the corresponding concept. And, after reading these definitions (as well as the reams of collateral literature made available by numerous vendors), if you are like me, you are probably asking one or both of the following questions: "Doesn't this stuff sound very familiar?" and "Aren't these all parts of the solution to the same problem?"
If I am not mistaken, the concepts addressed by CDI recall the same kinds of ideas embodied in the push for customer relationship management (CRM) - or, is CDI a way of moving the CRM concept a step further? Is master data management a new name for what we used to call "reference data," or is there some qualitative difference? EII sounds like earlier attempts at combining application integration techniques with knowledge collaboration. That reminds me of a lot of the conversations focused on grid computing a few years back. Not only that, if we take a customer-only subset of MDM and add EII to it, don't we get CDI?
Even though this is oversimplifying the distinctions between these different acronyms, one might be suspicious of this being a case of trying to get old dogs to do some new tricks. On the other hand, good ideas never go out of style, and the more we understand about the way humans perceive and consider the transformation of data to information, the more we start to see how maturation of approaches combined with cross-pollination of ideas may provide better insight as to how to actually achieve the actionable 360-degree view of a customer, product, location, etc.
Because of my combined experience in high performance computing and data integration, all three of these areas are familiar and of interest to me. The apparent trend seems to be an alignment of approaches to aggregating data sets from multiple sources, consolidating semantic information and enabling the real-time delivery of a logical presentation of information objects attributed by their various collected characteristics. What is really new and what are just older approaches blessed with new buzz-names?
Where do we go from here? Because there may be some confusion about these different application areas, it is worthwhile to expend a little energy to get a better understanding of what these tools are trying to achieve, what differentiates them from their predecessors and what enhances the information consumer's ability to exploit and potentially monetize an organization's information asset. In addition, there is an opportunity to explore ways to enhance these approaches, to evaluate how they dovetail with information modeling and exchange frameworks, and any related data quality issues. Lastly, as the technology matures, it would be interesting to compare and contrast conceptual approaches that emerge as favorites in the marketplace. Over the upcoming months, I intend to dedicate column space to these topics. If you have any specific questions, comments or suggestions, please contact me at email@example.com.
For more information on related topics visit the following related portals...
Customer Data Integration,
Enterprise Information Integration (EII) and
Master Data Management.
David Loshin is the president of Knowledge Integrity, Inc., a consulting and development company focusing on customized information management solutions including information quality solutions consulting, information quality training and business rules solutions. Loshin is the author of Enterprise Knowledge Management - The Data Quality Approach (Morgan Kaufmann, 2001) and Business Intelligence - The Savvy Manager's Guide and is a frequent speaker on maximizing the value of information. Loshin may be reached at firstname.lastname@example.org.