In the beginning there was just raw data... rows and columns of numbers in strict, structured, disciplined formats generated by a variety of transactional and operational business systems. The volume - while quite large - was still manageable. And it was good. Well, good enough at least. Then, the “content
Everyone around SAS seems to be buzzing about big data and high-performance analytics (HPA). As we're preparing for conferences, product launches and customer engagements, it's the main idea on almost everyone's mind. Along with that excitement and buzz, however, it's worthwhile to step back and look at how we got here, and
I just had a great conversation about big data and high-performance analytics with Eric Williams, retired CIO of Catalina Marketing, and I hope to publish some of what he had to say here in the next few weeks. In the meantime, you can learn a lot about how big data
Back in my day-one post of this "HPA once a day project," I promised a post about Twitter as "big data." I know some of you are already moaning about the noise on Twitter and the "what I ate for breakfast" type of commentary that's prevalent there. So I'm going to
I'm not a fan of obscure acronyms in blog post titles, but by the end of this month I'm hoping HPA won't be obscure to anyone who reads this blog. It stands for high-performance analytics, and I'm challenging myself to blog about it once a day for the next month.
That there is a growing shortage of analytical talent in most of the economies of the world is clear. In a May 2011 report, the McKinsey Global Institute put some numbers on the demand: “By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with
The tools for analytics are getting more sophisticated as data becomes more voluminous, says Jim Sterne, President of Target Marketing, in the video below. The real magic still comes from human ingenuity, explains Sterne, but it helps to give analysts the tools they need to make that magic happen. Hear
It's true. "Big data" can be a problem and an opportunity. Many organizations have struggled to manage, much less profit from, the deluge. In 2012, look for big data to spur demand for big data analytics. New developments in high-performance computing as well as increased demand for visualization and text
Big data has been a hot topic recently, but more often than not the topic is covered from an IT perspective. What do the analysts, data miners and statisticians think? I recall the old days discussing with statisticians what data mining is and how it fundamentally differs from statistics. In
In 27 years at SAS, Keith Collins says his whole career has been about scaling to the enterprise. He wonders, "Why now do we call it big data? What will the next generation call it? Bigger data?" Keith led a panel of business leaders at the Premier Business Leadership Series
