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Mark Troester 5
IT, analytics & the speed of knowledge

I recently spent some time with Eric Williams, former Executive Vice President and CIO of Catalina Marketing, to prepare for a whitepaper that he is writing on IT, analytics, innovation and business value. As always with Eric, it was a fascinating discussion so I thought I would blog about some

Mark Troester 0
Cloud Expo NYC (and of course...Big Data)

I recently attended the Cloud Expo in New York City where big data was a key topic. Keeping with the various topics addressed at the event, here are my thoughts as they relate to the Cloud Expo. Warning: if you are searching for strong conclusions or straightforward advice, you’ll need

Mark Troester 1
Alignment enables analytic success

Analytics Infrastructure: Vision & Strategy Consideration #1 (Part 1 of 15 considerations for Analytics Infrastructure) In a perfect world, the entire organization would be aligned, and the analytics vision would be driven by top down, executive leadership. Since we aren’t living in a perfect world, it often takes work to

Mark Troester 3
Analytics Infrastructure: 15 Considerations

I recently presented with Jessica Dunn from Bank of America at the SAS Global Forum Executive Conference. Our presentation addressed the considerations necessary to build and manage an effective analytics infrastructure. Although we both worked on our presentations separately before we had a chance to discuss teh session, we built

Mark Troester 0
Hadoop's Potential to Rewrite Data Management

Well, it's certainly a provocative title, and hopefully it will be a thought provoking conversation. I am participating in a panel discussion along with Philip Russom of TDWI, David Menninger of EMC, and James Markarian of Informatica. The discussion will be hosted by DM Radio hosts Eric Kavanagh and Jim Ericson. The interview occurs

Mark Troester 1
Big data quality: Think outside the box

In my last post I set the stage for data quality considerations for big data. Today, I’ll cover the following big data and data quality considerations: Data quality efforts should be "fit for purpose" Extend data quality by thinking “outside the box” Data quality efforts should be "fit for purpose"

Mark Troester 26
SAS Hadoop - A peek at the technology

Thanks for returning to learn more about this critical technology. Following yesterday’s overview post on the new SAS Hadoop support, we’ll dig a little deeper today and consider the following: Under the Hood: A Peek at the Technology SAS Hadoop Value Summary A Note About the Future Under the Hood:

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