SAS Voices
News and views from the people who make SAS a great place to work
We’ve been talking about data recently at the Analytic Hospitality Executive. I’ve advocated to use whatever data you have, big or small, to get started today on analytic initiatives that will help you avoid big data paralysis. In this blog, I’m going to get a bit more technical than usual
What's that productivity related quote by Charles Dickens? "My advice is never do tomorrow what you can do today." For years, machine learning has been written about and discussed widely with a focus on the benefits it will bring in the near future. But guess what? The future for machine learning
There's a lot of talk right now about the Internet of Things and how it's likely the prime catalyst for the digital transformation of organizations over the next few years. Billions of sensors, and devices with sensors, all generating data in a hyper-connected world where it can be easily shared
I’ve had a lot of discussions with business leaders around the discrepancy between big data investment fears and successful use cases. Most of them say that "the quest for the golden use case" takes too much time and is usually not successful in the end. Ultimately, this quest can lead to
Technology has brought the world a great deal of good, but the downside is that we’re increasingly vulnerable to some seriously scary stuff: Terrorists taking control of airplanes through the in-flight entertainment system. Governments breaking into secure systems and stealing identities. Thugs messing with the steering of self-driving cars. When
Dust off that old aphorism about an ounce of prevention. Oil companies applying analytics for predictive maintenance can see a substantial downtick in the unanticipated equipment repairs that quickly eat into an oil well’s profitability. Maintenance is far from a trivial concern in the oilfield. A pumping oil well is
