Analytics Across the Enterprise is a new book authored by IBM analytics practitioners Dr. Brenda L. Dietrich, Dr. Emily C. Plachy and Maureen Fitzgerald Norton that details IBM’s past and present leadership in business analytics.
http://ibm.co/5stepsThis big question looms whenever and wherever practitioners all join together to discuss advances, changes and needs in the industry. While, in some ways, the answer is “yes"—because there is a need, a desire and a significant opportunity—in many ways healthcare organizations
The recent controversy over the ethics of Facebook's attempts to influence moods through tweaks to its newsfeed algorithms is overblown. Essentially, Facebook data scientists conducted one of many real-world experiments that are standard operating procedure with them and with most online businesses
Video content analytics tools are humanity's unblinking eyes, capable of continuously filtering the world's media streams at scale. Video content analytics algorithms can parse the fine details within and between successive frames of specific streams, supporting pattern recognition, gesture
The Internet of Things is changing the way we live and do business: billions of connected devices are driving demand for new services, faster development of applications and real-time access to information; the consumer and corporate worlds are intermingling with multi-purpose devices that are
In an increasingly competitive and polarized marketplace with rising customer expectations, the traditional means of competitive differentiation are being challenged as never before. To respond, retailers need to evolve their focus to become customer-centric in both strategy and execution. This
Many make out the data scientist to be a Renaissance woman or man who can single-handedly elevate the organization’s analytics savvy. However, preparing students for corporate roles in data science means training them for many positions on a team. At Arizona State University, we work closely with
A data scientist uses machine learning (ML) to find heretofore unknown correlations and other patterns in fresh data. ML is adept at finding both the "known unknowns" and the "unknown unknowns" through the power of supervised learning and unsupervised learning methodologies, respectively.
The goal of moving beyond basic TV ratings and simple consumer demographics to establishing a secure analytics environment to integrate subscriber, set-top-box and third-party, enriched data in near real time is something leading media and entertainment organizations continue to embrace. After all
Research from International Customer Management Institute (ICMI) reveals that only 25 percent of companies feel that their customers are "extremely engaged." How, then, can companies increase customer engagement to cultivate fans? Is creating the same passion in customers as sporting teams a myth?
The need for a data scientist is all the rage right now. At every marketing conference I go to, companies are clamoring for their skills, but the supply and demand is not coming to the needed equilibrium. We are faced with the choice of continuing to wait, or to employ a solution that is already at