Business Intelligence (BI)—that collection of technologies used to analyze data from different business systems in order to reveal meaningful insights about a company’s operations—is among CIOs’ top spending priorities, according to Merrill Lynch’s CIO Spending Survey.
It’s no wonder. Even a limited investment in BI software can yield compelling returns. Companies use BI to improve their decision-making, cut costs and identify new business opportunities. BI is more than just corporate reporting and more than a set of tools to coax recalcitrant data out of enterprise systems. Leading-edge CIOs are using BI to identify inefficient business processes that are ripe for reengineering.
Although BI holds great promise, implementations can be dogged by technical and cultural challenges. You have to ensure that the data feeding your BI applications is clean and consistent so that users trust it, and you want users to embrace these tools. Our range of content on BI will show you how companies are getting a competitive advantage from it and what you need to do to ensure smooth deployments and user acceptance.
Business Intelligence: Not Just for Bosses Anymore
Business intelligence has long been about spitting out data—often irrelevant and outdated—to a few big bosses. But today’s BI is both more meaningful and more egalitarian. And it requires ever tighter alignment between IT and the business.
The Brain Behind the Big, Bad Burger and Other Tales of Business Intelligence
Business intelligence systems have, for the most part, been dreary failures. But not in the restaurant industry. There, the payoffs have been significant.
Business Intelligence Gets Smart(er)
Companies are using business intelligence software for more than simple data mining. They’re using it to identify hot sellers, cut costs and discover new business.
**Irving Tyler, profiled in this story, answered readers’ questions about his use of Business Intelligence at Quaker Chemical.
Boiling Up Data
On a wider scale than ever before, energetic hunters and gatherers collect raw data and throw it in the pot before anyone else gets a good look. Then they cook it into a dubious information stew.
More and more companies are using analytics to drive their decision-making processes. But there’s a right and a wrong way to do it.