The SAS Data Science Blog
Advanced analytics from SAS data scientists
When you work with big data, you often deal with both a large number of observations and a large number of features. When the number of features is large, they can be highly correlated, resulting in significant amount of redundancy in the data. Principal component analysis can be a very
Ok, so the title is a little provocative, but some people are dubious that data science training is even possible, because they believe data science entails skills one can learn only on the job and not in a classroom. I am not in that camp, although I do believe that data
My last post, Pitching analytics: recommendations on how to sell your story, discussed the steps I consider when winding up for an analytics pitch. In part 2 of this series I share the tips and tricks I have acquired for throwing strikes for during your analytics pitch. Like everyone, sometimes
Have you been in your attic lately? Or maybe cleaned out that closet that all of your “stuff” seems to gravitate to? Sure, mostly you’ll just find old junk that is no longer useful or purely nostalgic, but every once in a while you come across those long lost treasures
Gartner has stated that there are nearly five billion connected devices throughout the world today and predicts that there will be more than 25 billion by 2020, making the potential of this technology unlimited. The connected devices in industrial settings, in personal devices, and in our homes are creating a
I’ve often heard people say about weather forecasters “they have the best job…they just report what the models are telling them, and when they’re wrong they can always blame it on Mother Nature throwing us a curve.” While that’s true, this glass-half-empty crowd is failing to appreciate how amazing the