Dr, Magnus Kuschel of Volvo Truck recently spoke on an Automotive News Power Training webinar describing how Volvo Truck is using IBM big data and analytics capabilities to unlock new insights from telematics data.
Judging by the interest level—the webinar blew away all previous attendance records
Bedside manner is something that some physicians have in spades and others totally lack. It’s not just a matter of personalities, etiquette and social pleasantries. Depending on the patient’s situation, it can make as much difference as medication, therapy and surgery in influencing whether
CMOs are enhancing their abilities to contribute not only to the marketing of new products, but also in their development, design, sale and support. These are all data-centric functions that are working together, today to drive business success.
Since big data is still relatively new technology, many of you are conducting research and seeking quality educational resources. That's apparent in this list of the 10 most popular analyst reports, ebooks and white papers. We are proud to offer such an extensive library - more than 40 items - from
Co-authored by Kim Minor, Worldwide Industry Marketing Manager for Insurance at IBM.
Claims fraud is an important topic, so we’ve written about it several times before. In this blog, I want to discuss how IBM big data capabilities can augment an existing fraud system at any insurer. By wrapping
The top 10 blogs from the first half of 2013 show you are interested in learning how to get started with big data – especially if you’re in the banking industry – and looking at just what it is that gives a data scientist that elusive star power. It’s also clear that good blog posts have long legs
How CSPs are Transforming Call Centers to Lower Churn, Costs and Stress
The day in the life of a call center agent can be very stressful, especially when information needed to solve the customer problem is not accurate, not up-to-date, not consolidated and not immediately available. Slow service
We’re continuing our look at the most popular content on IBM Big Data Hub for the first half of 2013. Here are the most-watched videos.
Big Data, Big Opportunities for Communications Service Providers
Big Data, Big Opportunities: Energy & Utilities
T-Mobile: Network Engineering Success
With one half of 2013 behind us, let’s take a look at what has been on the top of your mind over those six months. All week long, we will be reviewing the most read, most watched and most listened to content on IBM Big Data Hub. Today, we’ll look at the top 10 most popular podcasts.
Top 5 Big
Here’s a big data problem for you. Let’s say you’ve accidentally traveled back in time 30 years and the only way to get Back to the Future is to transfer 1.21 Gigawatts of energy into a beat-up DeLorean.
Well, back in 1985, the solution, by Hollywood standards of course, was the
"To boldly go where no man has gone before."
With that straightforward phrase, Captain Kirk inspired not just the crew of the Starship Enterprise, but all of us to follow him on an incredible journey. He exuded confidence that came from not being afraid to explore. In that spirit, I offer 4 new
After a successful promotion, a consumer products company minimizes OOS and maximizes sales
In April, I introduced a video demonstration called Optimizing Consumer Product Promotions Effectiveness with Analytics. In this demo we met Mary, the marketing brand manager for DuraBar, a nutritional bar
With multiple channels and numerous ways to interact with companies, today’s customer journey is a complex weave of paths. Often, customers start and end their journey before the business is even aware of it. With today’s competitive market place, the companies that best understand their customer–
Interest in big data remains high. In fact, according to the 2012 study “Analytics: The real-world use of big data” that surveyed more than 1100 executives and practitioners from 95 countries, 75 percent of organizations have big data activities underway.
But that same study also uncovered two
Analytics solutions designed to handle the volume and variety of data available today also help insurance companies improve catastrophe risk modeling, through which companies determine the exposure of current policies and predict the probable maximum loss (PML) from a catastrophic event.