That's no easy task. The BI application lexicon is vast: Performance management applications. Online analytical processing tools. Querying and reporting. Data mining. Business analytics and dashboards. Decision support systems. Data warehousing. All of these critical functionalities can be (and usually are) grouped under the business intelligence umbrella by vendors.

But the relative robustness of each vendor's offerings as well as the architectural and technology differences among the software applications and the business users they will likely serve can be starkly different.

BI Users Must Define Their Priorities

That pervasive uncertainty places the onus on business users and IT departments to figure out exactly what types of information they need to extract from their BI systems, say analysts.

"You basically have to figure out what items interest you, and what's important to you," says Walter Lee, an analyst at Burton Group. Therefore, companies must formulate a BI requirements strategy, or methodology, as Lee terms it, that is based on the analytic and reporting data that will best synch with their overall business strategy. But that too can be difficult, Lee notes. "It can be a convoluted and lengthy process."

Even when IT departments are able to hammer out the back-office integration and data-sharing complexities (which are not trivial), many companies still struggle to get business users to actually use the BI applications.

A February 2008 Gartner report on self-service options for business intelligence concluded that users find BI tools difficult to use and consume. "Anecdotal evidence suggests no more than 20 percent of users in most organizations use reporting, ad hoc query and online analytical processing tools on a regular basis," writes Gartner's Schlegel. He also notes that most IT departments are overwhelmed with BI requests to meet business requirements and often have difficulty building BI applications due to a shortage in developers' skill sets.

"Lack of both end-user and developer skills is frequently cited as a major barrier when deploying BI applications," Schlegel writes. "In both cases, there is a need to make analytical applications easier to build and consume, to overcome this skills gap."

Burton Group's Anderson doesn't take exception to the 20 percent usability rate, though he does note that that number is common in many application deployments outside of BI. "If you have a complex problem and user interface, no matter how well written it is there's only a certain amount of people who are going to use that tool," he says.

But a sizeable challenge with BI tools right now is ensuring that the data and analytics that are ultimately presented to users are meaningful and actionable by those users.