Startups know that what customers say they want isn’t necessarily what they want. The same principle is critical to the success of your BI project.
Yellowfin benefits from a few core design decisions -- or "fortuitous mistakes," as CEO Glen Rabie puts it -- that make it a surprisingly adaptable BI platform.
How can the principles of branding be applied to BI to help multiple groups in large organizations work collaboratively across departmental boundaries?
With SAP Predictive Analysis, the company says it wants to bring predictive analytic capabilities to as many users as possible.
Predictive analytics and big data "make perfect sense together," says analyst Fern Halper, even as some vendors are struggling to catch up with users.
MPP databases have to scale out and scale up. According to analytic database specialist Calpont, they don't. Most focus on MPP to the detriment of SMP.
Three recommendations for improving customer intelligence and engagement.
Modern predictive analytics tools and solutions are no longer restricted to IT specialists. Don’t let these five myths impede your adoption of this powerful technology.
The increased interest in predictive analytics points to its power and possibilities, says analyst Fern Halper. Vendors are eagerly jumping on board, and open source is becoming increasingly important.
Successful project opportunities share five features so developers can achieve business success.
Don't just deliver bad data faster. Improve data in real time.
Knowing how to get started is key to building a successful project -- and obtaining the funding to get the project off the ground.
QlikTech's Donald Farmer discusses how mobile technologies are fundamentally changing BI, sometimes in ways you might not expect.
Why are so many data integration players selling enterprise service buses of their own? Is it just a matter of vendor opportunism?
The search for BI insight already has a game-like feel to it. Advocates of "gamification" want to amplify this effect and immerse BI users in their task.
Data governance is more than just managing data in order to optimize outcomes.
This three-step approach will help you establish or reenergize your DI development projects.
There are many traps to rolling out an enterprise-wide BI project. We show you how to avoid those problems.
How are BI maturity assessments implemented and how can their value be marginalized? We explore the impact and scope of such assessments and what to expect from the process.
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.