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Reality mining : using big data to engineer a better World

By: Material type: TextTextPublication details: New Delhi PHI 2016Description: vi,199 p. 22cm ; HBISBN:
  • 978-8120351882
Subject(s): DDC classification:
  • 006.312 EAG
Online resources: Summary: Big Data is made up of lots of little data: numbers entered into cell phones, addresses entered into GPS devices, visits to websites, online purchases, ATM transactions, and any other activity that leaves a digital trail. This book on Big Data cuts through the hype to explore the potential of Big Data. It shows the ways in which the analysis of Big Data can be used to improve human systems as varied as political polling and disease tracking, while considering user privacy. The authors describe Reality Mining at five different levels: the individual, the neighbourhood and organization, the city, the nation and the world. For each level, they first offer a non-technical explanation of data collection methods and then describe applications and systems that have been or could be built. Thus, making it understandable to everyone. Some examples are a mobile app that helps smokers quit smoking; a workplace “knowledge system”; the use of GPS, Wi-Fi, and mobile phone data to manage and predict traffic flows; and analysis of social media to track the spread of disease. Their argument being how Big Data, used respectfully and responsibly, can help people live better, healthier, and happier lives.
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Big Data is made up of lots of little data: numbers entered into cell phones, addresses entered into GPS devices, visits to websites, online purchases, ATM transactions, and any other activity that leaves a digital trail. This book on Big Data cuts through the hype to explore the potential of Big Data. It shows the ways in which the analysis of Big Data can be used to improve human systems as varied as political polling and disease tracking, while considering user privacy.

The authors describe Reality Mining at five different levels: the individual, the neighbourhood and organization, the city, the nation and the world. For each level, they first offer a non-technical explanation of data collection methods and then describe applications and systems that have been or could be built. Thus, making it understandable to everyone. Some examples are a mobile app that helps smokers quit smoking; a workplace “knowledge system”; the use of GPS, Wi-Fi, and mobile phone data to manage and predict traffic flows; and analysis of social media to track the spread of disease. Their argument being how Big Data, used respectfully and responsibly, can help people live better, healthier, and happier lives.

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