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Mark Troester 9
Big data defined: It's more than Hadoop

Volume, Variety, Velocity – how many times have you heard that lately? The “3 V’s” are commonly used to describe big data by various vendors and analysts. Forrester extends this by introducing “Variability” as a 4th V – this addresses the fact that you need to design for agility due

Mark Troester 1
Research announcement for analytics in the cloud

Talk about a collision, what can be more hyped now than analytics and the cloud - unless you throw in "big data," and well, quite honestly, that's related too! SAS co-sponsored research on predictive analytics in the cloud with James Taylor and Decision Management Solutions. The research focused on the

Mike Ames 21
SAS, Hadoop and big data

The term “big data” is all the rage right now, however the term “big” is relative. At SAS we have been called on to do “big data” projects and more importantly “big analytics” projects for many years now. In fact, we are the pioneers of analytics on “big data.” There is

Alison Bolen 0
Big data reality check

I'm always a fan of moving beyond the buzz, so the new research from Nucleus Research, "Big Data: Beyond the Buzzwords," caught my eye. Besides providing a quick, simple definition ("big data is all about creating, analyzing, and managing large data sets"), The 3-page report does a nice job distilling

Mark Troester 2
Prove It!

I was fortunate to participate in the SAS Power Series event that was held in Minneapolis recently. This event brought together seasoned analytic users from a variety of companies to share their experiences, successes and challenges as they strive to leverage analytics to help drive their business. Although the business

Becky Graebe 1
"It's not possible, but what if it were ..."

As big data grow beyond buzzwords, leading organizations are looking to innovators who understand the possibilities and can help them do something useful with all that information. Yesterday at The Economist's Ideas Economy: Information conference being held in Santa Clara, California, attendees heard from some of the industry’s most knowledgeable

Alison Bolen 2
What type of big is your data?

The basic big data problem is simple to understand: we create too much data to store and analyze it all. The problem gets bigger, however, when you consider the related factors: our problems themselves are getting bigger, the analytics needed to solve them are more complex and the data is

Mark Troester 0
Would you rather analyze or prepare?

Are you one of those people that love doing analysis? If so, there is nothing quite like analyzing customer patterns, revenue trends, inventory levels, cost optimization, etc. -- especially when you can use that analysis to make changes that will optimize your business. But before you can start the analysis,

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