The gaming business moves fast. Casinos serve a multitude of entertainment options to thousands of patrons 24 hours a day, a pace that results in a myriad of interaction points with their patrons. Competition in this service industry is fierce. If patrons at a casino do not feel that
Do you “buy and build as you go” with your analytics architecture? Most companies do, and have for decades. The result is a heterogeneous environment for analytics with a variety of hardware, software, databases and analytical applications used in silos. There’s tremendous duplication of data and inconsistency in the analytical
In part 1 of this series we looked at how to acquire personal data from the Internet of Things for our own exploration. But we found that the data was not yet ready for analysis, as is usually the case. In this part, we will look at how we can use SAS
How can you use an innovation lab to be as agile and innovative as a startup? Are there different types of innovation labs and if so what is the difference? I answered these two questions in previous posts, and now I will answer a third pressing question: how can you build the business
Everything’s bigger in Texas and that definitely held true at SAS Global Forum 2015. The conference was bigger and busier than ever, especially for the education industry. There were so many amazing presentations and announcements, that you may have missed a few -- here are the highlights. We had a several customer presentations on SAS Visual
We’ve all been there. You’ve knuckled down, cleaned out the garage, the attic, and that cupboard under the stairs, thrown away a ton of stuff, only to need it again the very next week. Until recently, that’s exactly what many businesses did with their data. The data explosion has radically
Have you noticed how your smart phone seems to know everything about you? Where you live, where you work, and even how long your daily commute will take! A lot of that information is generated by your daily activities while using your connected devices. There is much to be found by analyzing the
Insurance relies on the ability to predict future claims or loss exposure based on historical information and experience. However, insurers face an uncertain future due to spiraling operational costs, escalating regulatory pressures, increasing competition and greater customer expectations. More than ever, insurance companies need to optimize their business processes. But
Today’s natural language processing (NLP) systems can do some amazing things, including enabling the transformation of unstructured data into structured numerical and/or categorical data. Why is this important? Because once the key information has been identified or a key pattern modeled, the newly created, structured data can be used in
On Monday, SAS announced the beginning of a new era with its Toshiba Global Commerce Solutions OEM partnership. This is the first time SAS has provided its technology for an equipment manufacturer to wrap into its solution to help retail customers gain the benefits of advanced analytics. We always ask
