You can Measure practically anything in the age of Social media, but if you don\'t know what you\'re looking for, collecting mountains of data won\'t yield a grain of insight.
He is also co-founder and former Chairman of Fisheye Analytics..
Previously he was a Professorat INSEAD, a leading graduate business school.
He has an MBA from INSEAD as well as an MS in quantum physics from TU Berlin (Germany).
SOUMITRA DUTTA, an authority on the impact of new technology on business, is the dean of the Samuel Curtis Johnson Graduate School of Management at Cornell University.
He is a popular public speaker on business Analytics and serves as an advisor and board member at several data-centric corporations in Europe and the US.
Lutz is a highly regarded technology executive who built a sales center for Dell Europe as well as an incubator for mobile applications at Ericsson.
He\'s also co-founder and former CEO of Fisheye Analytics, a Media data-mining company whose products support governments and various NGOs, such as the Organisation for Economic Co-operation and Development (OECD) and the International Olympic Committee, which was acquired by the WPP group.
About the Author: LUTZ FINGER, a director at Linked In, is an authority on Social Media and text analytics.
With this book, these two experts provide business managers and analysts with a high-level overview of the Ask-Measure-Learn system, and demonstrate specific ways to apply Social Media Analytics to marketing, sales, public relations, and Customer management, Using examples and case studies.
Authors Lutz Finger and Soumitra Dutta originally devised this system to help governments and NGOs sift through volumes of data.
This non-technical guide shows you how to extract significant business value from big data with Ask-Measure-Learn, a system that helps you ask the right questions, Measure the right data, and then learn from the results.
You can Measure practically anything in the age of Social media, but if you don\'t know what you\'re looking for, collecting mountains of data won\'t yield a grain of insight
