Diego Saenz, the founder of Data Driven CEO, has over 20 years of experience as a management consultant, corporate executive and entrepreneur. In his current role, he provides Big Data Analytics consulting, speaking and training. He talked with us on the topic “Can Big Data Stem Churn?”
Now that the hoopla surrounding the big data “Smart Sixteen” has subsided, let’s scrutinize the victor, Predict Customer Behavior, to understand why it dominated the other contenders as the top big data consideration. What key factors makes this big data initiative most appealing? Would it be the
The weekly #cxo Twitter chat explores the customer experience and how businesses can optimize their operations, analytics and service with big data. Join the #cxo tribe on Twitter every Monday at 12:00 p.m. ET.
Chief marketing officers are evolving to bring creative- and data-driven marketing and advertising together in order to deliver relevance to consumers and discover deeper insight into audiences. In this podcast, Graeme Noseworthy explains the top issues that CMOs reported in a research study they
Seattle Children’s Hospital is a demonstrated leader in innovative research and therapies for children, as shown below in just a few of their most recent announcements.
Seattle Children’s Research Institute, one of seven members of the Dream Team uniting researchers across the country in
Companies that insure our road vehicles request information including the driver’s age, gender (no longer legal in Europe), claims history and the ZIP or post code where the vehicle is parked at night. On this narrow data set, insurers construct an analytic model used to assess and price risk. A
Data Exploration is one of the top five business use cases for big data. Stacy Leidwinger, product marketing manager for IBM Data Explorer, describes the challenges that many organizations face, and the four key steps they should take when beginning a data exploration project.
To learn more about
Organizations are discovering that their continued relevance, and even survival, depends on harnessing big data to better understand their customers, reduce risk, and discover entirely new opportunities for growth in a changing world. On April 3rd, IBM announced exciting innovations that help
Seattle Children's Hospital, one of the leading children's hospitals in the U.S., needed a solution to manage and extract valuable insights from vast amounts of complex data. Working with business partner Brightlight Consulting, Seattle Children's implemented the IBM PureData for Analytics solution
Hadoop is fundamental to the future of big data. Users are adopting Hadoop for strategic roles in their current data warehousing architectures, such as extract/transform/load (ETL), data staging and preprocessing of unstructured content. Hadoop is also a key technology in next-generation massively
Join Stacy Leidwinger, Product Manager IBM Big Data for a discussion of way Big Data can deliver an enhanced 360 degree view of the customer. This is the second in our series examining popular use cases for Big Data.
In last month’s post, I talked about how cognitive computers, like IBM Watson, have the ability to do what the earliest underwriters did: approach each risk individually and, based on historical learning, apply reason and judgment to determine a rate. Cognitive computing allows insurers to analyze
Audience measurement is experiencing dramatic change from a focus on the channel to a focus on the individual as marketers and advertisers work to understand the 360-degree view of the customer. What advantage does this provide to marketers and advertisers? If marketers need data-driven audience
This live video chat, "Big Data Management: After the Launch," featured an interactive discussion moderated by Jeffrey Kelly, Principal Research Contributor at Wikibon.org and a Contributing Editor at SiliconANGLE; James Kobielus (IBM), Nancy Kopp-Hensley, Sr. Program Director for IBM PureData
Organizations in the petroleum industry are no strangers to large volumes of data. With the right technology solutions, these companies can move beyond traditional real-time monitoring to more agile real-time prediction. By rapidly analyzing incoming technical and business data—and applying that