With so much complexity and change in the marketplace, organizations worldwide are leveraging opportunities to make better predictions, identify solutions and take strategic, proactive steps forward – which means that they increasingly depend on big data. In their quest for organizational resilience, however, companies find that numbers aren’t necessarily the secret
“Dear Cat, I got an email from my IT department that says: [We are nearing capacity on the Flotsam Drive. Please clear data from any folders you are no longer using so we can save disk space. Thanks, The IT Department] Doesn’t this strike you as a bit old-fashioned? I
Outside, the Cary, NC sky is gray and winds are blowing freezing rain, but a group of statisticians at SAS are channeling warm green hills and the soft, gold light of a California evening. Team conversations alternate between distributed processing, PROC IMSTAT and how many pairs of shorts to pack.
“Dear Cat, In a repeated measures drug study, I am unsure what to do with the baseline measurement. Since it is one of the time points in my study, I feel like I should use it as one of the dependent variable measurements. But I have seen analyses where baseline
“How can we begin to make sense of the unstructured data, when we still don’t make the most of our structured data?” said the exasperated senior manager from a large retail firm. One of the great pleasures of my job is the relationship with students that continues after class has
Happy New Year!! This is a good time to think about what was going on here in SAS Education one year ago, and to introduce you to a big project that I'm really excited to "take public." In January 2010 (as well as throughout 2009), we kept getting cries for
Have you used multivariate procedures in SAS and wanted to save out scores? Some procedures, such as FACTOR, CANDISC, CANCORR, PRINCOMP, and others have an OUT= option to save scores to the input data set. However, to score a new data set, or to perform scoring with multivariate procedures that