News & Blogs
Harvard Business Review
September 18, 2012 – Increasingly, the largest retailers in markets across the country are employing sophisticated personalized marketing and thereby becoming the primary shopping destination for a growing number of consumers. Meanwhile, other retailers in those markets, once vigorous competitors for those loyalties, are being relegated to the role of convenience stores.
Fast Co Exist
September 18, 2012 – A data-mining project that adapts analytics used by Amazon and big box retailers to predict customer behavior is now being used to stop terrorism before it starts. The analytic technologies that the University of Maryland team applied to terrorism are similar to data mining analytics commonly used by Amazon and big box retailers to predict customer activity.
September 17, 2012 – ING Direct wanted to get into the heads of customers, so the bank started a data-collection initiative to gain a deeper understanding of how it was interacting with customers. Now, years later, ING Direct faces the problem of having too much data, and is trying to make sense of all of the information in a useful and cost-effective way. Thus far, ING Direct has already spent in the range of AU$4 to AU$5 million on data analytics alone.
September 17, 2012 – Big data is going mainstream, but there are still plenty of lessons to be learned from Silicon Valley data scientists whose businesses depend on data to survive. Although their use cases don’t always align with what more-traditional businesses are doing, they know enough about the science and technology to save big-data newcomers a lot of frustration.
September 14, 2012 – During a talk earlier this year at the Big Data for the Public Good seminar series, Stamen's Eric Rodenbeck emphasized that data scientists are not only researchers, but also storytellers. Fittingly, many in the field boast a cross-disciplinary background, such as Greenplum's Noah Zimmerman, who moonlighted at Stanford's design school while doing PhD research on immunology and statistics. This intersection of science, art, and storytelling is vividly illustrated in the work of Eric Fischer, a former Google engineer whose data-driven mapmaking is as visually stunning as it is revealing.
September 14, 2012 – As organizations invest in analytics, predictive analytics is becoming a focus area. These advanced, mathematically based approaches are a powerful tool for leveraging data. Meanwhile, organizations are tackling the challenges of big data, handling more data in more formats that arrives and changes more quickly than ever before. As this tidal wave of data comes crashing down, traditional approaches to storing and managing data are being challenged.
September 14, 2012 – This fall, prestigious Columbia University in New York City is offering a course entitled “Introduction to Data Science,” taught by a team under the direction of Google Statistician and Columbia Assistant Professor Rachel Schutt. The class is an outgrowth of the recently-created Institute for Data Sciences and Engineering, a joint initiative between Columbia and New York City.
September 13, 2012 – Petabytes of information, predictive analytics, visualizations of global trends and activity…sometimes the humans producing all this information seem obscured. The Human Face of Big Data, a project by Against All Odds Productions and sponsored by EMC, aims to tell some of the human stories revealed from massive database clusters. With the term Big Data becoming increasingly ubiquitous and misunderstood, the project provides answers to two basic but key questions: where is all the information coming from, and how is it affecting our lives?
September 13, 2012 – For a company like Ford the promise of big data revolves around analyzing internal information from repair logs and sensors. Michael Cavaretta, Ph.D., technical leader of predictive analytics and data mining at Ford Research and Innovation, sees big data as a technology that can solve a lot of internal issues.
Harvard Business Review
September 13, 2012 – Do your employees have the skills to benefit from big data? As Tom Davenport and DJ Patil note in their October Harvard Business Review article on the rise of the data scientist, the advent of the big data era means that analyzing large, messy, unstructured data is going to increasingly form part of everyone's work. Managers and business analysts will often be called upon to conduct data-driven experiments, to interpret data, and to create innovative data-based products and services. To thrive in this world, many will require additional skills.