Big Data at Work: Dispelling the Myths, Uncovering the Opportunities Author: Visit Amazon's Thomas H. Davenport Page | Language: English | ISBN:
1422168166 | Format: EPUB
Big Data at Work: Dispelling the Myths, Uncovering the Opportunities Description
Review
ADVANCE PRAISE for Big Data at Work:
Jane Griffin, Managing Director Analytics, Deloitte Canada and Americas—
“Big Data at Work is the first and only book to describe how real organizations are using big data, extracting value from it, and combining it with other forms of data and analytics. It’s an invaluable guide to planning and action.”
Jonathan D. Becher, Chief Marketing Officer, SAP—
“Is Big Data a buzzword or does it have practical applications in business? Big Data at Work goes beyond tech-talk to help businesspeople turn Big Data into Big Decisions.”
Gary L. Gottlieb, MD, MBA, President and CEO, Partners HealthCare System, Inc.; Professor of Psychiatry, Harvard Medical School—
“Big Data at Work provides a terrific foundation for thoughtful planning to exploit the business opportunities created by diverse and vast sources of information. Davenport’s clear approach will enlighten managers about the need to carefully mine these resources to improve operations and products while driving new and competitive strategies.”
Rob Bearden, CEO, Hortonworks—
“Thomas Davenport has supplied a smart, practical book for anyone looking to unlock the opportunities—and avoid the pitfalls—of big data.”
Adele K. Sweetwood, Vice President, Americas Marketing & Support, SAS—
“Conversational, engaging, and an exceptional guide for decision making in the big data world. Big Data at Work offers insight to the business and technology components of a big data strategy, a path to success, and best practices from across industry sectors.”
About the Author
Thomas H. Davenport is a world-renowned thought leader on business analytics and big data, translating important technological trends into new and revitalized management practices that demonstrate the value of analytics to all functions of an organization. He is the President’s Distinguished Professor of Information Technology and Management at Babson College, a fellow of the MIT Center for Digital Business, cofounder and Director of Research at the International Institute for Analytics, and a senior adviser to Deloitte Analytics. Davenport is the author or coauthor of seventeen books, including the bestselling Competing on Analytics, as well as the author of dozens of articles for Harvard Business Review.
- Hardcover: 240 pages
- Publisher: Harvard Business Review Press (February 25, 2014)
- Language: English
- ISBN-10: 1422168166
- ISBN-13: 978-1422168165
- Product Dimensions: 9.2 x 6.2 x 0.9 inches
- Shipping Weight: 1 pounds (View shipping rates and policies)
Big data, at least today, requires some educated faith. ROI is difficult to define in advance--particularly when it involves new products and services or faster decisions, according to Thomas Davenport in this book. Nonetheless, some businesses are getting significant benefits from employing data scientists to work on Big Data, so it definitely seems to be something worth investigating.
Although the idea of Big Data is not precisely defined, the characteristics of Big Data described by the author include unstructured formats, volume of greater than 100 terrabytes, existing in a constant flow rather than a static pool, analysed by machine learning rather than hypothesis, and intended for data-based products rather than internal decision support. These are trends rather than absolutes, as Big Data includes more conventional types of data as well.
The key to deriving maximum advantage from Big Data seems to involve employing the smartest data scientists to analyse the data. Good data scientists are likely to be rare and expensive, given the ideal traits described by the author:
* Understanding of big data technology architectures and coding
* Improvisation, evidence-based decision making and action orientation
* Strong communication and relationship skills, particularly in dealing with senior management
* High level skills in statistics, visual analytics, machine learning, and analysis of unstructured data
* Good business sense and focus on commercial value
The book assiduously avoids using technical language, and as a result the book avoids answering some of the questions raised in readers' minds.
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