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on phones, the devices installed in homes and workplaces that monitor
everything from power consumption to the activities of families and
workers, and the constant streams of social-media tweets, postings, and
messages. In fact, one can safely conclude that big data results from the
intimate connection that companies and governments recognize between
cloud computing and smart devices.
Cloud providers have also led the way in promoting big-data analysis,
viewing it as a means of expanding revenue. Some companies simply
enable big data by introducing analytics programs to the applications they
provide their cloud-computing customers. Other companies go further
by directly analyzing the data they store on workers and customers to
ind added value. One irm produced a national database on employees
who have been caught stealing, information that retailers use to prevent
future hiring (Clifford and Silver-Greenberg 2013). Another irm used
consumer data to develop a predictive algorithm to let clients know what
iles its users are most likely to download to local storage. Still others are
“productivizing” data by harnessing publicly available archives such as
Twitter postings to build new products (Wainewright 2013). This has
been the centerpiece concept behind IBM's Smarter Analytics project,
a combination of software, systems, and strategies that enable clients
to combine their own business or enterprise data with their consumers'
unstructured data to better identify and anticipate consumer behavior.
IBM refers to the latter as “the data of desire” because it registers popular
expressions of sentiment and feeling, such as likes/dislikes, about products
and services. This gives its cloud customers the ability to correlate sales
records with social-media postings, thereby linking behavioral data with
information about customer feelings to provide a deeper view of customer
sentiment—not just which customers are buying, but why. IBM credits
this system with enabling a communication carrier to predict which
customers were likely to defect within ninety days and reduced churn by
35 percent in the irst year (IBM 2013). The potential in big data gives
traditional companies like IBM opportunities for reinvention. A leader
in research on embedding intelligence and communication capabilities in
objects, or what is called the “Internet of things,” General Electric has
also bet heavily on transforming itself into a company that specializes in
inding big-data solutions in the cloud (Butler 2013b). So has Monsanto,
one of the world's leading chemical and agribusiness companies and the
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