In-Depth

BI Marketplace: What’s in Store for ‘04

Niche specialists will find themselves competing against stronger companies that have acquired their struggling competitors. Organizations need to make contingency plans.

• By Stephen Swoyer
• 02/04/2004

Analysts who’ve looked into their analytic crystal balls to determine what’s in store for 2004 are seeing a rerun of 2003. Among the trends continuing into this year: more business intelligence (BI) consolidation (though not as much as last year), and a further convergence of BI markets and functionality areas.

Writing in a market prospectus for 2004, Kevin Strange, a vice president and research director with Gartner Inc., predicts that consolidation will continue, albeit at a slower pace, and speculates that over the coming year, leading-edge technology adopters will concentrate primarily on the skills and planning that are essential for successful BI implementations.

This is partially because the vendors involved in last summer’s blockbuster acquisitions—namely, Business Objects SA and Hyperion Solutions Corp.—are still fleshing out their integration strategies with respect to the rest of their product lines. “Enterprises that are evaluating BI vendors' road maps may find it easier to select BI and data warehousing technologies once the consolidated companies reconcile their product lines,” he writes, adding: “Vendors not involved in mergers and acquisitions may appear more stable, but also may be distracted by potential consolidation.”

This is especially true for smaller vendors and niche specialists, notes Mike Schiff, a senior analyst with consultancy Current Analysis Inc. “As this [acquisition] trend continues into 2004, and we expect that it will, the niche specialists will find themselves competing against stronger companies that have acquired their struggling competitors,” he writes. “And while in prior years strong technology sometimes disappeared when a company was failing, this technology is now, more often than not, being salvaged by stronger companies that recognize its value and can afford to make further investments in it.”

What this means, Strange argues, is that organizations that deploy solutions from non-dominant players must develop contingency plans, just in case a vendor is acquired by a larger competitor. “Enterprises must be circumspect about selecting a vendor and develop contingency plans against the possibility that the vendor will be acquired. Enterprises should also plan for the resulting functional and market convergence,” Strange writes.

Elsewhere, says Strange, companies are coming to terms with the fact that if they want to exploit strategic BI initiatives, they’ve got to focus more heavily on simplifying their underlying BI infrastructures, which are typically populated with a hodgepodge of BI solutions that don't interoperate. “A rigid and inflexible infrastructure that cannot be upgraded or modified will not maintain its value,” he writes.

At the same time, Strange and his firm believe that organizations have their work cut out for them as they attempt to engineer flexible BI solutions from inherently inflexible infrastructures. “Enterprises must not underestimate the challenges and complexity related to delivering the data infrastructure required to support strategic BI initiatives,” he cautions.

Strange advises organizations to take an inventory of their tools and technologies, and says this process should also include an attempt to assess the value of the data they’re collecting. “A process is only as effective as the data that supports it,” he counsels, recommending a strong dose of data quality in 2004: “[C]ompliance with government regulations and cutting redundancy from business operations will depend on improving data quality.”

Current Analysis’ Schiff, too, thinks that compliance efforts and other concerns will cause organizations to focus like a laser on data quality in 2004.

“Data quality and data profiling will become upfront requirements rather than applied after-the-fact when analysis errors are traced back to poor data quality,” he argues. “It is now well-recognized that quality data is essential to all analysis and that ‘garbage-in, garbage-out’ applies to both operational and decision-support systems.”

Over the last several years, grid computing has emerged as a strategy for supporting the massive scaling of applications and ratcheting up application efficiencies. In 2004, Strange writes, many IT organizations should consider grid-based solutions for certain applications. “[Leading-edge] enterprises should closely monitor pioneering grid computing efforts to support extremely large volumes of data and explorations of powerful, complex analytics applications,” he says.

Finally, Current Analysis’ Schiff believes that data mining will emerge as a key technology in 2004, prompted largely by compliance concerns. “[Sarbanes-Oxley and HIPAA] regulations, combined with compliance rules such as the Patriot Act … will drive the need to quickly bring together, store, and analyze disparate data sources and will continue to fuel all segments of the data warehouse market,” he concludes. “Data mining, perhaps under the new nomenclature of predictive analytics, will prove its worth in true 'bet your border' situations.”