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Mark Troester 2
Data Integration is old news!!

This may be controversial coming from someone that has worked with data his entire career, someone that has been involved with software vendors focused on data integration and access for the last 6 years, and someone that is responsible for product marketing for SAS data management capability, but I’ll say

Mark Troester 3
Top 10 IT considerations for analytics in 2012

It’s hard to believe, but now that 2011 is almost over it’s time to look ahead. The technology pundits are starting to publish their 2012 predictions, and it’s not surprising to see topics like analytics, cloud, big data, mobile, social networking, virtualization, open source on these lists. Instead of creating

Matthew Magne 0
Three pillars of better business outcomes: information management, analytics, and campaign optimization

Lately, in consulting with customers about SAS solutions, I’m increasingly seeing discussions revolve around 3 inter-related but distinct segments: Information Management, Analytics, and Campaign Optimization. In the past, these discussions might have happened with 3 different audiences in 3 different meetings, but we are seeing a massive convergence across these

Mark Troester 3
Who’s right? Business or IT

I’ve had many recent opportunities to discuss the role of IT and business based on recent research efforts, focus group conversations, customer visits and advisory board discussions. Some of the feedback is really striking and sadly comical – “They don’t get it, they don’t understand analytics” – I heard the

Mark Troester 2
Big Hype requires solid Big Data tenets

Big hype about big data has played a significant role in driving awareness about the value of analytics. SAS welcomes the interest in big data, since it highlights our ability to work with huge volumes of complex and diverse data. Since this is such a critical topic, we have formulated

Mike Ames 3
Big Data why now?

Ask any data warehouse architect what is driving the “big data” craze and he’ll tell you it has to do with the cost of storage and the advancements in distributed computing and most likely will mention Hadoop. Most enterprise data warehouses are constrained by cost and scalability of relational databases.

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