Big Data Research
July 30, 2014
This new series covers big data adoption across multiple industrial sectors, as well as the defining big data elements and anomalies prevalent across each sector.
July 28, 2014
In the rapidly evolving SQL-on-Hadoop space, IBM’s Big SQL 3.0 moves the industry forward through its contributions in improving query performance and workload management, while maintaining compatibility with open source Hive and SQL standard. This blog gets under the hood to explain how Big SQL 3.0 delivers these optimizations.
July 23, 2014
A majority of organizations today claim they have a competitive advantage because they are using big data and analytics. But, if everyone is claiming that, who really has the competitive advantage? The ones that do more predictive analytics? The ones that can do it cheaper? My bet is that it’s the ones that can do it faster.
July 18, 2014
If most organizations are using analytics to improve customer interactions, optimize supply chains and reduce financial risk then where does the advantage in today's marketplace come from? The IBV 2014 Analytics study will explore how organizations are creating a competitive advantage in today's data-driven marketplace.
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.