I love San Francisco in the spring. Itís even better when one of the major analytics events in the country -- SAS Global Forum -- chooses Moscone Center as the venue. Dungeness crab, dim sum, and data analytics are a hard combination to beat.
Iím here for the week, and Iím really looking forward to it. It looks as if we're going to have great weather the entire time, and there are some great talks lined up. Big names in analytics like Billy Beane and Tom Davenport are here along with attendees from all over the world. What brings us all together?
Well, itís an exciting time to be in analytics. When I talk to executives from various industries, they all have one theme related to analytics: in essence, that analytics will fundamentally change the way they do business. In fact, one top executive at an international consulting firm (yes, you would know the name) recently told me that he believes in five years his firm will be making its money very differently than it does today. Analytics is his consultancy's future. That's why I, along with a few other thought leaders, was invited to speak to a gathering of the firmís leadership brought in from every region of the world -- to help it succeed in that future.
I, too, believe that analytics will transform our lives and businesses. These technologies will help us live more healthily and more safely. They will help us understand our world in ways undreamt of just a few years ago. They will help us conduct business more efficiently. And they will help us in ways we havenít thought of yet. In many ways, the transformation has already begun.
Part of what is driving this evolution is that the field of analytics itself is changing. Analytics is no longer just reports, cubes, and dashboards. Statistics is no longer just for academics. And we are all swimming in a rising tide of data. Advances in analytics are occurring on what seems like a daily basis.
I'm giving a talk this afternoon at SAS Global Forum (SGF to veteran attendees) on a set of technologies that represent the vanguard of that evolution. I recently began working hands-on with some of the latest high-performance analytic software and hardware, and I got to see the difference firsthand. The heart of high-performance capability lies in enabling data scientists to solve real-world problems with massive amounts of data using massively parallel processing (MPP). MPP allows us to break problems into many parts and then solve each of those parts at the same time -- in parallel. This approach can reduce run times from hours or days to minutes or seconds. How?
Imagine if I asked you to count the words in this blog. It might take you three or four minutes to get an accurate result. Now imagine you have a lot of friends to help you, and you can give each one of them a different sentence. And letís say you have another helper who can quickly tally the results from each of your friends. Voila! You can now solve the problem in a fraction of the time because you are all working in parallel on a different piece of the problem. Thatís how MPP works.
Iíll be going into a lot more detail in my talk, "High-Performance Analytics: Big Data Brought to Life on the EMC Greenplum Data Computing Appliance," at 2:00 p.m. PT, so if you're here I look forward to seeing you. Donít be shy about introducing yourself afterwards! And if you couldnít make it to San Francisco for SGF, you can still see some of the presentations over the web. Enjoy!
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