By 2012, emerging technologies will make it easier to build and consume analytical applications lessening IT's role in building these applications, according to Gartner, Inc.

"Evidence suggests that BI is used aggressively by just 15 to 20 percent of business users. For the BI sector to thrive, it needs to overcome the fact that most business users feel BI tools are hard to use," said Kurt Schlegel, research director at Gartner. "Other technologies, such as personal productivity, collaboration and Internet search have been widely adopted by mainstream users in both their business and personal lives. BI has the same opportunity for massive adoption, but it must overcome its well-earned reputation of being difficult to use."

Much of the innovation in the BI space will come from emerging technologies that will make it easier for users to build and consume their own reports and analytical applications. In particular, five technologies--interactive visualization, in-memory analytics, search integrated with BI, software as a service (SaaS) and service-oriented architecture (SOA)--will help drive mainstream BI adoption.

"However, as a result of this innovation, individuals and workgroups will be less dependent on central IT departments to meet their BI requirements," said Mr. Schlegel. "BI teams need to understand how to leverage these emerging technologies to drive BI adoption, but do it in a way that doesn't undermine the organization's existing BI architecture and standards."

Interactive visualization will be quickly accepted during the next two years as a common front end to analytical application, driven by the ubiquity of rich Internet applications. This technology trend will make reports and analytic applications easier and more fun to use. With its attractive display, it should be more widely adopted by users who aren't accustomed to the grid style of analysis and reporting offered by relational databases and spreadsheets. By definition, interactive visualization enables users to perform typical BI tasks, such as data filters, drill down and pivots, with little training by interacting with the visual, such as clicking on a pie wedge, or circling the dots on a scatter plot.

Because BI explores huge amounts of data, it has traditionally relied on IT to build aggregate and summary tables to optimize performance on disc-based data storage. This requirement to build a performance layer impeded self-service BI. Falling memory prices and the prevalence of 64-bit computing is making in memory analytics a more attractive alternative. With this approach, business users no longer require IT to build a performance layer.

Search integrated with BI can drive adoption in two ways. The first approach is to apply search to enable users to find existing reports. Most organizations use a hierarchical folder navigation structure to find reports. Finding reports is a challenge, considering most large organizations have hundreds or thousands of reports that were built autonomously with almost no regard for common naming conventions. Replacing hierarchical folder navigation with search will make it much easier for users to find existing reports. The second approach, which is just emerging, promises to help users find information from structured sources when a report doesn't exist. Applying a search index to structured data sources, rows and columns, is emerging as way for end users to perform their own ad hoc exploration of the data.

Many BI systems hold thousands of reports in a complex hierarchical structure. Users find it easier to find reports with search technologies backed by sophisticated relevance rankings instead of a folder navigation structure. Search will make it easier for users to find data for ad hoc queries although it will not help with related tasks such as formatting reports consistently.

Smaller companies that lack the base of investments in BI systems will increasingly turn to service companies to deliver services that integrate, analyze and report on data from numerous systems. Wider adoption of SaaS business models will make analytical applications more widely used, particularly among midsize companies. However, even large companies with full BI and data warehouse teams will embrace the SaaS model for some aspects of BI. The best example today is in Web site analytics, where business users--typically in marketing--can access very sophisticated reports and analytic applications of Web site activity with virtually no need for IT by leveraging a software as a service provider. The increasing trend toward business process outsourcing and cloud computing will only accelerate this trend, enabling the delivery of BI-related information and analysis for particular subject area domains via the SaaS model.

SOA, coupled with a move toward a model-driven architecture, based on a visual "drag-and-drop" development style, will make it easier to build BI applications. A proliferation of this drag-and-drop style of development will drive resurgence in departmental analytical application development. This will, in turn, encourage adoption and usage, but also has the potential to engender more rogue deployments that buck standards set by a central BI team in IT.

Gartner analysts will further discuss the impact of emerging technologies on BI at the Gartner Business Intelligence Summit being held April 1-3 at the Hyatt Regency Chicago. The Gartner BI Summit is the only event designed to provide businesses with the knowledge required to create a visionary business intelligence strategy. This event focuses on the methodologies, strategies, technologies and architectures that will move organizations from the tactics of cost cutting and compliance to increasing their agility and responsiveness, and improving overall business performance.
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