Big Data Research
July 17, 2014
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 these days. This was just a routine real-world experiment in big-data-driven sentiment analysis, content optimization and customer experience management.
July 3, 2014
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 recognition, location detection, motion detection, event detection, production-style detection, dynamic video masking and camera tamper detection.
June 26, 2014
The date is June 26, 1969. Mankind is getting ready to launch three brave astronauts into space; two of which will walk on the surface of the moon and change history forever. Meanwhile, another change is taking place: the rise of the computer in the workplace and the importance of applying data to decision making at high speed and high capacity across long distances. Such is the case in the world of advertising. Join us as we take “one small step” back in time to experience “one giant leap” in the origins of big data.
June 20, 2014
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 means personalizing every stage of the customer’s path and this can be done by leveraging big data and analytics.
June 12, 2014
Real-world experimentation of a very personal and hyper-analytical nature is what the quantified-self (QS) movement is all about. QS practitioners are playing with approaches that behavioral scientists have traditionally applied to third-party subjects within controlled laboratory experiments. The scientific establishment is beginning to realize the potential of quantified self tools for gaining primary data directly from human subjects in a way that is organic to the biological, behavioral, and psychological phenomena being studied.
June 5, 2014
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.
May 30, 2014
With IBM’s latest release of cloud capabilities, we’ve once again taken our analytics offering to another level positively impacting all areas of the organization including the front-office, back-office, business units and executive suite. This cloud-based solution stack provides users ready access to the information they need whether they’re in or out of the office. In addition, we’ve added new user-friendly analytic discovery and visualization tools and cross-platform social capabilities while enabling users to customize their dashboards and reports to see their analytics the way they want to see them with simple drag-and-drop actions. This is a must-see moment in the evolution of cloud capabilities.
May 29, 2014
If I'm about to offend your religious sensibilities, I apologize in advance. Please avert your eyes from this post.
May 28, 2014
Today’s data-driven organization is faced with magnified urgency around data volume, user needs and compressed decision time frames. In order to address these challenges while maintaining an effective analytical environment, many organizations are exploring cloud-based environments coupled with powerful analytical technology to accelerate decisions and enhance business performance.
May 15, 2014
Open sourcing of all climate data would give humanity a continuously updated baseline environmental intelligence metric that could be used to track deterioration or improvements in key areas (air, water, pollution, soil) over time.