Technology changes are helping us analyze growing data volumes. Our data warehousing architecture must remain flexible, and frequent validation of user requirements and data usage will help us achieve this goal.
What new technologies are affecting BI professionals, and how can we be prepared for these changes and the innovations they bring?
Host Analytics says its cloud pedigree gives it advantages relative to its on-premises competitors in corporate performance management.
Predixion's goal was to develop a solution that makes data mining and predictive analytics consumable and usable by rank-and-file workers. Has it succeeded?
How do organizations effectively handle the inevitable challenges in human dynamics to ensure project success?
Which key BI trends matter most? Cindi Howson explains the top seven innovations she and co-presenter Dave Stodder will discuss at the Cool BI Forum in Chicago in May.
Three catalysts that are changing BI and data warehousing.
A decade ago, using spreadsheets to manage ETL source mappings might've made sense. Today, an upstart BI vendor claims, it isn't just inelegant -- it's anachronistic.
Thanks to a combination of social, mobility, cloud, Big Data, and other forces, business intelligence and data warehousing are on the cusp of profound transformations. The question is: which way are these technologies headed?
Microsoft bids "adios" to OLE-DB.
Huge data sets can reveal hidden patterns, analyst explains.
A long-time tech observer delves into why some companies succeed and others fail.
Line-of-business analysts are advancing on IT's old territory. Five thoughts on what it means for both parties.
For a company that's best known as a provider of back-end plumbing, Tibco's tibbr and Spotfire solutions comprise a very visible public face.
Hadoop is still misunderstood by many BI professionals.
MeLLmo's Roambi BI platform runs only on Apple's iOS platforms. Is that a risky position or a savvy one?
It’s a tough time to cost-justify BI projects and get buy-in from upper management. Here’s how to get your data quality project approved.
With so much written about cloud and BI in the last year, it would seem the intersection of these two hot IT trends must be a winner -- but is it?
Vendors appear to be making an effort to address concerns about how they price their data integration tools. Will their efforts result in meaningful savings?
What's behind the increasing popularity of data mining, and what is its relationship to predictive analytics?