RESEARCH & RESOURCES

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Come Together: Business Intelligence and Enterprise Content Management Bleed into Each Other

Thanks to a number of trends, enterprise content management (ECM) now has a legitimate business intelligence (BI) aspect -- or vice versa.

Neither technology dominates the other, but tendrils of both are bleeding into one another. Although no one’s talking convergence, most analysts concede a kind of limited commingling is occurring.

“[It] depends on what you think content management is. Germaine to BI and DW, search and text analytics continue to be used, and used more. These technologies contribute directly to BI and DW,” observes Philip Russom, senior manager of TDWI Research, the research arm of TDWI.

That said, Russom stresses, bread-and-butter BI and bread-and-butter content management are two wholly different disciplines: “A content management system -- which largely shoves around lots of textual documents -- has relatively little direct contribution to BI and DW.”

One obvious way in which content management can and does contribute to BI and DW involves the growing importance of unstructured or semi-structured data.

Thanks to the growth of social networking applications, online forums, instant messaging, collaborative tools, and similar technologies, data of this kind -- which (prior to the advent of Sarbanes-Oxley and other data-retention-heavy regulatory mandates) might well have been discarded -- is fast becoming mission-critical. These days, market watcher Gartner Inc. estimates that unstructured content accounts for up to 80 percent of the information in any given organization. Factor in the growing popularity of domain-specific applications that consume or generate unstructured content -- such as customer support and satisfaction, brand or reputation management, media monitoring, and/or risk management software tools -- and you have a big unstructured or semi-structured data brew, which we’ll call “quasi-structured” data.

That’s why content management has specific applicability in the data management (DM) arena: in addition to the well-defined structured (that is, relational or hierarchical) information that has long been their mainstay, DM groups are increasingly collecting and managing quasi-structured information, too.

Call it a reversal of fortune. For a long time, after all, DM pros didn’t know what to do with such data -- it wasn’t deemed a good fit for conventional databases. That’s why content management vendors, which (as Russom points out) used to deal chiefly with physical documents or with document facsimiles, stepped into the void, along with storage players (such as EMC Corp.), which saw a lucrative opportunity in the terabytes of quasi-structured that were fast accumulating in most enterprises.

Nowadays, many organizations have come full circle. They’re hip to the idea that quasi-structured information is arguably most valuable when it’s brought into an enterprise DW so that users can simultaneously query both structured and quasi-structured information. In this scenario, users consume and analyze quasi-structured content in tandem with structured content, giving them a Bigger Picture of enterprise activity.

The Content Management Connection

If DM groups have come (however grudgingly) to endorse quasi-structured data, content management vendors have also warmed to BI. Industry veteran Seth Grimes, for example, points to the intersection of content management, search, and text analytics. ECM vendors have embraced text analytics, in particular, as a kind of silver bullet that helps enhance the “findability” of quasi-structured information for business processes. This usage is likely to grow, Grimes says.

“Media and publishing systems [including search engines] use text analytics to generate metadata and enrich and index metadata and content in order to support content distribution and retrieval,” writes Grimes, a principal with consultancy Alta Plana, in Text Analytics 2009: User Perspectives on Solutions and Providers. Right now, 20 percent of adopters use text analytics to complement their content management strategies, chiefly, “to enhance the findability of content for business processes that include compliance, e-discovery, and claims processing,” Grimes notes.

Finally, software vendors are doing their best to lead users, too. Gartner, for example, cites the influence of a quintet of vendor heavyweights -- Hewlett-Packard Co. (HP), IBM, Microsoft, Oracle, and SAP AG -- that market competitive content management and creditable DM software and service offerings. These vendors all appear in Gartner’s Magic Quadrant survey, with IBM, Microsoft, and Oracle joining both EMC Corp. and Open Text Corp. in the “Leaders” quadrant (HP and SAP, on the other hand, are ECM “Niche” players, according to Gartner).

Not coincidentally, all five vendors field credible BI and data warehousing offerings, too. No software vendor passes up a chance to cross-sell into an existing customer environment, and it’s a safe bet that these players are targeting customers with combined database, data integration, business intelligence, and content management pitches.

Elsewhere, Gartner says, content management is moving away from the quirkiness or niche status that has long defined it. In other words, content management vendors are shifting to tackle vertical-specific technology issues that -- by virtue of their tendency to intersect with other technology domains such as enterprise resource planning (ERP) or customer relationship management (CRM) applications -- take them far afield from what has been called ECM.

“Fewer [content management] vendors will focus on bundling generalist functions -- such as imaging, library services, and document collaboration -- leaving these functions to infrastructure vendors. Most vendors will instead focus on adding value by bundling specific functions as ‘base configurations’ -- vertical or horizontal solutions that are integrated with industry, ERP or CRM applications,” write Toby Bell, Karen Shegda, Mark Gilbert, Kenneth Chin, and Mick MacComascaigh in Gartner’s most recent Magic Quadrant for Enterprise Content Management.

About the Author


Stephen Swoyer is a technology writer with 20 years of experience. His writing has focused on business intelligence, data warehousing, and analytics for almost 15 years. Swoyer has an abiding interest in tech, but he’s particularly intrigued by the thorny people and process problems technology vendors never, ever want to talk about. You can contact him at [email protected].

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