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
Bank Systems & Technology just published a special issue focused on "big data" - and how high-performance analytics helps solve the big data problem. Clicking on the cover image will take you to the ebook, so you can flip through 24 pages full of information about the benefits of big data for banking.
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.
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
At the NRF BIG Show in NYC this week, one of the hottest topics is what retailers can do with high-performance analytics. One major retailer has been able to determine optimal prices for as many as 270 million items each week, from 30 to two hours, run advanced markdown optimization
What brings more than 20,000 retailers to NYC in mid-January? I can promise you, it’s not the balmy 15 degree temperatures -- it’s the 101st NRF BIG SHOW, where SAS is a platinum sponsor. This is my first year attending this event – and it’s a bit overwhelming, so here’s a
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
The Premier Business Leadership Series in Orlando was the backdrop for a number of news announcements from SAS. Here's a rundown: 1. Big Data research A new survey has found that organizations with formal data management strategies derive more value from data assets and outperform competitors. The survey, Big Data:
I jotted down the following fact from a session yesterday at the Disney Analytics & Optimization Summit: Organizations that invest in analytics perform better in the market. That's quite an assertion. Tweetable for sure. But it was a late-afternoon presentation and I was hungry for supper. So I forgot about
The promise of high-performance analytics, as I understand it, is this: Regardless of how you store your data or how much of it there is, complex analytical procedures can still access that data, conduct a series of calculations on that data and provide answers quickly, accurately and using the full
Rome was not built in a day. Similarly, high-performance analytics is a product of many cumulative architectural, computational and analytical advances. The ability to solve complex business problems by applying algorithms from multiple disciplines to increasingly large volumes of data of all types - both structured and unstructured - is
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
~Contributed by Becky Graebe, SAS Communications Manager~ If there was any doubt in the minds of SAS Global Forum attendees that the computing landscape has changed remarkably in recent years, Vice President of Platform R&D Paul Kent and Research Statistician Developer Oliver Schabenberger set that idea squarely off the grid
