Reader Colin White contends, "While there is no question that a bidirectional CDI hub is valuable technology for integrating customer data, it is important to realize that CDI is only one step and one possible starting point in the journey toward managing enterprisewide master data."
CDI Is Not MDM
In "The Next Wave of Data Management" (July 2006), Jill Dyché and Evan Levy state, "Central to the concepts of CDI [customer data integration] and MDM [master data management] is the existence of a hub, which functions as the point of reconciliation for data across a company's heterogeneous systems and applications."
While there is no question that a bidirectional CDI hub is valuable technology for integrating customer data, it is important to realize that CDI is only one step and one possible starting point in the journey toward managing enterprisewide master data. CDI solutions integrate customer master data, but frequently don't manage it. They may not provide support for complex master data hierarchies and relationships, master data versioning, historical master data, master data lineage reporting and so on.
My concern is that CRM and data warehousing experts are frequently driving CDI projects in isolation. They often don't have the required enterprise perspective to move the CDI project toward true enterprise MDM, and the result will therefore be a CDI silo.
Enterprise MDM is about more than just integrating customer data and data warehousing. MDM involves other types of master data both for BI and operational processing. An MDM system is responsible for managing and supplying master data to both business transactions and BI systems.
It will take time for organizations to get to full enterprise MDM. It is important, therefore, to have a strategic MDM plan, even if the MDM system is built iteratively from the bottom up.
COLIN WHITE President BI Research email@example.com
Authors' reply: We agree that the management piece of MDM is a challenge. But if tasks like data matching, standardization, error detection and correction, hierarchy management, rules and semantics enforcement fall under the rubric of data management--and they do--then CDI and MDM automate not only data integration, but also data management. Indeed, data management means standardizing rules, models and processes so they're repeatable. CDI hubs are getting well-deserved buzz for these capabilities, and executives are more likely to support and fund the integration and management of customer master data to support customer-focused strategies. CDI is likely to be the best on-ramp for an enterprise MDM program--hardly an isolationist approach.
Defining Web 2.0
The reason Josh Greenbaum hates Web 2.0 (see Application Insight, August 2006) is that he doesn't understand it. He mentions how he likes to wander in a library. How is a library's structure different from the Web? There are categories, an index and an order to the arrangement of knowledge--things that are like each other are next to each other.
That's what Web 2.0--the Semantic Web--is all about: the ability to let Web pages relate to each other by content. It allows us not only to build structure inside the content, but to provide hooks to knowledge outside the document.
JOHN BAILO The Texeme Construct myspace.com/texeme
Author's reply: The problem is that your definition of Web 2.0 is different from others out there (such as participatory Web and social Web). And there's Web 2.0 the service mark, Web 2.0 as a reason to get venture funding and so on. The Semantic Web is a great idea, but "Web 2.0" is really Bust 2.0 about to happen.
The Agile ArchiveWhen it comes to managing data, donít look at backup and archiving systems as burdens and cost centers. A well-designed archive can enhance data protection and restores, ease search and e-discovery efforts, and save money by intelligently moving data from expensive primary storage systems.
2014 Analytics, BI, and Information Management SurveyITís tried for years to simplify data analytics and business intelligence efforts. Have visual analysis tools and Hadoop and NoSQL databases helped? Respondents to our 2014 InformationWeek Analytics, Business Intelligence, and Information Management Survey have a mixed outlook.