Achieve an impressive ROI using i-based reporting and BI software to connect users to the latest Web 2.0 technology.

Written by Bill Langston

Editor's Note: This article is a distillation of the Webcast "Migrating from IBM Query/400?" which is available free from the MC Press Webcast Center. It also covers information from the white paper "Replacing Query/400: Understanding Your Options," also available free from the MC Press White Paper Center.

Recent IBM announcements and acquisitions in the business intelligence (BI) market might lead you to think your company must be one of the few not yet embracing predictive analytics, data warehousing, or cloud computing for BI. In reality, most mid-size companies today rely on a mix of queries, reports, file transfers, temporary databases, and spreadsheets to help them make business decisions and share information.

Economic uncertainty is putting more emphasis on making smarter business decisions. Business intelligence tools, which can help, offer more choices than ever for System i shops.

Written by John Ghrist

One of the most important areas in which computing is being applied to business activity is in the realm of business intelligence (BI). From humble beginnings such as merely displaying an enterprise's financial results, BI has grown to become an exciting array of products and methods for analyzing business data and for making decisions about an enterprise's future directions, a process generally referred to as business performance management.

More than just a replacement for Query/400, DB2 Web Query is business intelligence light.

Written by Chris Smith

In one of the sessions on DB2 Web Query at the OCEAN User Group's Technical Conference this week, the speaker, Doug Mack, asked for a show of hands of those users who had installed the product and those who had actually started to use it. I looked around to see the results: installed DB2 Web Query--quite a few hands; used it--not so many.

Data warehousing can add significant value by facilitating enhanced business intelligence, but success isn't automatic. This article explores critical data-warehousing success factors.

By Henry Martinez

Operational databases are predominantly optimized for transaction processing. They are usually highly normalized and are very efficient at reading and writing a few related records at a time. However, they are typically not optimally architected to serve the needs of executives and business analysts who perform query, reporting, and analysis against vast swaths of data. When these people use operational databases to complete these tasks, the database must often perform large, complex table joins. The necessary disk I/O and processing can bring systems to their knees.

Disparate data can inhibit value creation, but data integration best practices allow organizations to fully leverage the inherent value in their information resources.

By John Gay

Silos of disparate data plague many companies. The reasons for the data diversity vary: organizations may run best-of-breed applications on the most appropriate platform for each product; in the days of client/server computing, the responsibility for choosing applications may have been decentralized, with different departments choosing different platforms; a merged company may use a variety of different applications, keeping separate some of the formerly individual companies' activities and the software that supports those parallel activities, while choosing the best of the predecessor companies' applications to serve those business functions that are merged. And the list goes on.