Business Intelligence encompasses all aspects of gathering, cleansing, mining, storing and analyzing data as well as disseminating the insights to the right decision makers. Data warehousing and analytic modeling are as much a part of a BI strategy as are visualization tools and digital dashboards.
Published: April 2013
When making choices about the deployment of a business intelligence system, an organization needs to ask questions, including: How much technology support is likely to be required for a particular solution? What are the limitations of a given platform?...(read more).
Published: November 2012
Let’s face it: When it comes to business intelligence (BI), a lot of organizations today are mouse hunting with an elephant gun.
An elephant gun means recruiting and training a team of database specialists to manage the...(read more).
Published: October 2012
Businesses of all sizes are turning to self-service business intelligence tools, particularly those that incorporate visualization and other advanced user interface techniques to achieve greater ease of use and faster and better access to information and insights. This is...(read more).
Published: October 2012
At some point over the last few years you’ve probably heard the expression “big data”, and maybe you even tried to look up the definition. You probably found nothing short of a dozen or so different conceptual frameworks and...(read more).
Published: September 2012
This Deep Dive analyst report identifies some of the catalysts driving technology innovation in business intelligence platforms and how this innovation is unleashing a new breed of sophisticated self-service reporting and analysis tools and capabilities. It explores how top-performing...(read more).
Published: May 2012
This Deep Dive analyst report examines the benefits of deploying a flexible foundation for business intelligence and analytics. It makes the case that business agility is enabled not only by the notion of Agile Business Intelligence, but also by...(read more).
Published: March 2012
Everyone is seeking ways to do more with less. Organizations with tight budgets are eager to look at any technology-enabled business initiative that has a chance of saving money or generating revenue. But they do not want to spend...(read more).
Published: October 2011
Not every business has the need, the desire, or the ability to embark on extensive and expensive BI efforts. Even the largest businesses often find that the most tangible return on investment comes from using relatively inexpensive tools that...(read more).
Published: March 2011
While still relatively small in terms of overall market penetration, open source solutions in the business intelligence (BI) realm have nonetheless been growing rapidly and gaining increased credibility. In addition to being affordable, open source solutions have some advantages...(read more).
Published: February 2011
Most providers of business intelligence solutions include dashboard capabilities within their software suites as a matter of course. In recent years, however, improvements in design have added tremendous flexibility to dashboards, and technical approaches to gathering data have given...(read more).
Published: January 2011
The promise of anywhere, anytime access to business information is becoming a reality for organizations with the initiative to exploit advances in mobile computing and business intelligence (BI) software. More and more capable smart phones and other mobile devices,...(read more).
Published: January 2011
This comprehensive 25-page benchmark report explores the elements of a successful BI strategy along with a full vendor landscape. Some of the best examples of rapid ROI from BI projects are associated with tactical implementations that emphasize immediate...(read more).
Published: January 2011
The word agile is widely used today within the business intelligence industry to describe a key aspect of business intelligence (BI) and business analytics (BA) delivery and use. Infusing agility – commonly defined as the ability to be quick...(read more).
Published: January 2011
Data quality is not a one-shot deal. It requires an ongoing effort that involves business users as well as IT staff. Data quality problems emanate from many sources and require ongoing diligence. A commitment to continuous data quality results...(read more).