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Big Data, the Second Generation

Planning Your Big Data Strategy

32,05 € Lieferbar in 5-7 Tagen


Big Data, the Second Generation gives business professionals the basic technological understanding, analytic tools, and diagnostic checklists they need to identify and plan out the big data strategy most appropriate to their particular company. This book examines the technologies and tools that are required to work at big data scale on the semi-structured and unstructured data of text analysis, speech recognition, video analysis, machine learning, and more.
We are fast entering the second generation of big data: namely, big data that is accessible to nearly all organizations, as opposed to a few big companies. This book systematically maps the MapReduce and Apache Hadoop 2 ecosystems to the second-generation array of big data business applications, provides you the guidelines to match your company's profile with suitable applications, and shows you how to boost the power of your business analytics with new technologies for the compression, visualization, and actionable analysis of big data.
The authors draw their insights into the second generation of big data from deep experience in industry as well as research. David Belanger is the co-leader of the IEEE Big Data Initiative and was previously the Chief Scientist of AT&T Labs. Rashmi Jain is her university’s representative in the New Jersey Big Data Alliance and was previously an IT systems architect for Accenture.
Belanger and Jain walk you through the business applications of big data techniques for mining data produced by communication networks, social networks, and communities of interest. They consider the critical governance and security issues raised when an enterprise ventures into the big data space. They forecast the business value of emergent trends such as big-data-as-a-service open platforms. Finally, they present an action plan for executives and managers in companies large and small that will deliver maximum ROI from applying big data techniques to proprietary and public databases.
A strategic planning guide rather than a technical implementation manual, Big Data, the Second Generation: Planning Your Big Data Strategy equips you to chart your organization’s roadmap to harnessing big data and big analytics to beat your competition in the race to higher topline sales and a fatter bottom line.


Titel: Big Data, the Second Generation
Autoren/Herausgeber: David Belanger, Rashmi Jain
Ausgabe: 1., st ed. 2016

ISBN/EAN: 9781484210147

Seitenzahl: 325
Format: 25,4 x 17,8 cm
Produktform: Taschenbuch/Softcover
Gewicht: 0 g
Sprache: Englisch

David Belanger is a Senior Research Fellow at Stevens Institute of Technology. In October 2014, he was appointed to the co-leadership of the three-year IEEE Big Data Initiative. He leads the Center for Big Data innovation at Stevens and is Stevens’ representative to the New Jersey Big Data Alliance. In August 2012, he retired from AT&T Labs where he was Chief Scientist and Vice President of Information, Software, & Systems Research of AT&T Shannon Labs. He built the Software Engineering Research Department which provided software tools and techniques used across AT&T Bell Labs and via open source across the world. He was the creator of the AT&T InfoLab, an organization aimed at optimizing the value gained from data within AT&T and a pioneer of Big Data research and practice. Belanger was awarded the AT&T Science and Technology Medal for his contributions in very large scale information mining technology and was named an AT&T Fellow for "lifetime contributions in software, software tools, and information mining." He received the Institute of Electrical and Electronic Engineers (IEEE) Communications Society Industrial Innovator Award and the Distinguished Engineer Award from the Association for Computing Machinery (ACM). As part of the Obama administration, Dr. Belanger chaired the Tech America Commercial Policy Board from 2011 to 2012. He is the author of the opening chapter of Big Data and Business Analytics (ed. Jay Liebowitz), "Architecting the Enterprise via Big Data Analytics." He took his MS and PhD in mathematics from Case Western Reserve University.

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