I’ve been monitoring an interesting discussion on the Big Data and Analytics group over on LinkedIn – “Is there a difference between big data and small data?” It is an interesting question, one that I’ve heard before during my travels down in the trenches as I explore our industry.
Richard Feynman, winner of the 1965 Nobel Prize in Physics and world renown “curious character,” gives us an insightful lecture about computer heuristics: how computers work, how they file information, how they handle data, how they use their information in allocated processing in a finite amount of time to solve problems and how they actually compute values of interest to human beings.
Here is an informative high-level presentation introducing Business Analytics by J. Michael Hardin, Ph.D. from the University of Alabama speaking at the SAS Global Forum 2013. The non-technical talk focuses on the conceptual issues surrounding business analytics and sets the stage for motivation behind using this technology. If you’re a decision maker in an organization […]
“Data has become the foundation upon which all smart business decisions are made. Archives have traditionally been inaccessible, offline and practically invisible. The new business culture demands more. The Dternity S unlocks the potential of your data, providing easy online access to all of your archived content.”
Stephen Wolfram, founder of Wolfram Research and creator of Mathematica, just announced the new Wolfram Programming Language. This new knowledge-based language could be a game changer in data science.
In this slidecast, Dimitri Williams from Ninja Metrics describes the company’s innovative Katana Social Analytics Engine. “Katana measures the value of social contributions in applications and games, provides detailed projections for the outcomes that matter to developers, and offers the tools to determine how effectively features facilitate engagement and social interaction.”
Big Data will change the way your organization responds to business opportunities. But to reap its full benefits, you have to move from proof of concept into full production. Here is an informative, 52-minute presentation that provides the guidelines for successfully integrating Hadoop into your standard data center processes.
Big Data & Brews reminds me of the good old pre-dotcom-bubble days when I used to attend many networking events over at the Westwood Brewery near UCLA. Those were heady days. It was beer and tech back then as it seems to be today. Now, instead of meeting up in person, you can enjoy contemporary discussions of the big data industry by watching the host, Datameer CEO Stephan Groschupf, and his guest in an informal pub atmosphere.
Jeremy Howard made a presentation to the Melbourne R meetup group, where he gave a brief overview of his “data scientist’s toolbox” (using a few Kaggle competitions as practical examples), and also provided an introduction to ensembles of decision trees (including the well-known Random Forest™ algorithm).