Data-ism: the revolution transforming decision making, consumer behavior, and almost everything else
(eAudiobook)

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Published:
[United States] : HarperAudio, 2015.
Format:
eAudiobook
Edition:
Unabridged.
Content Description:
1 online resource (1 audio file (6hr., 33 min.)) : digital.
Status:
Description

Steve Lohr, a technology reporter for the New York Times, chronicles the rise of Big Data, addressing cutting-edge business strategies and examining the dark side of a data-driven world. Coal, iron ore, and oil were the key productive assets that fueled the Industrial Revolution. Today, Data is the vital raw material of the information economy. The explosive abundance of this digital asset, more than doubling every two years, is creating a new world of opportunity and challenge. Data-ism is about this next phase, in which vast, Internet-scale data sets are used for discovery and prediction in virtually every field. It is a journey across this emerging world with people, illuminating narrative examples, and insights. It shows that, if exploited, this new revolution will change the way decisions are made-relying more on data and analysis, and less on intuition and experience-and transform the nature of leadership and management. Lohr explains how individuals and institutions will need to exploit, protect, and manage their data to stay competitive in the coming years. Filled with rich examples and anecdotes of the various ways in which the rise of Big Data is affecting everyday life it raises provocative questions about policy and practice that have wide implications for all of our lives.

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Language:
English
ISBN:
9780062397362, 0062397362

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Instant title available through hoopla.
Participants/Performers
Read by Walter Dixon.
Description
Steve Lohr, a technology reporter for the New York Times, chronicles the rise of Big Data, addressing cutting-edge business strategies and examining the dark side of a data-driven world. Coal, iron ore, and oil were the key productive assets that fueled the Industrial Revolution. Today, Data is the vital raw material of the information economy. The explosive abundance of this digital asset, more than doubling every two years, is creating a new world of opportunity and challenge. Data-ism is about this next phase, in which vast, Internet-scale data sets are used for discovery and prediction in virtually every field. It is a journey across this emerging world with people, illuminating narrative examples, and insights. It shows that, if exploited, this new revolution will change the way decisions are made-relying more on data and analysis, and less on intuition and experience-and transform the nature of leadership and management. Lohr explains how individuals and institutions will need to exploit, protect, and manage their data to stay competitive in the coming years. Filled with rich examples and anecdotes of the various ways in which the rise of Big Data is affecting everyday life it raises provocative questions about policy and practice that have wide implications for all of our lives.
System Details
Mode of access: World Wide Web.
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Citations
APA Citation (style guide)

Lohr, S., & Dixon, W. (2015). Data-ism: the revolution transforming decision making, consumer behavior, and almost everything else. Unabridged. [United States], HarperAudio.

Chicago / Turabian - Author Date Citation (style guide)

Lohr, Steve and Walter, Dixon. 2015. Data-ism: The Revolution Transforming Decision Making, Consumer Behavior, and Almost Everything Else. [United States], HarperAudio.

Chicago / Turabian - Humanities Citation (style guide)

Lohr, Steve and Walter, Dixon, Data-ism: The Revolution Transforming Decision Making, Consumer Behavior, and Almost Everything Else. [United States], HarperAudio, 2015.

MLA Citation (style guide)

Lohr, Steve, and Walter Dixon. Data-ism: The Revolution Transforming Decision Making, Consumer Behavior, and Almost Everything Else. Unabridged. [United States], HarperAudio, 2015.

Note! Citation formats are based on standards as of July 2022. Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy.
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37f47c6f-8c93-35be-776a-3bf896fc6432
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Hoopla Extract Information

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Last Grouped Work Modification TimeApr 17, 2024 06:34:42 AM

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