14 Chapter 1
A sizeable chunk of Big Data is analyzed, structured, and stored; but these pro-
cesses require skilled workers who tackle the time-consuming task of finding patterns
and drawing useful inferences in the reams of data they mine. In other words, big
businesses can devote considerable resources to making sense of Big Data. Those who
can afford to pay for data processing services profit from the expenditure, in terms
of increased workforce productivity, product development, and overall profitability
(Gravelle, “Maximizing” 1).
However, small businesses and individuals lack the resources to mine and make
sense of data-intensive scientific domains. The other side of the coin deals with the
constant streams of user-generated data on social media such as Facebook, Instagram,
Vine, Google+, and LinkedIn. Various manufacturers, employers, retail chains, enter-
tainment purveyors, governments, and the social media companies themselves are
able to collect and analyze useful data about individuals. Thus, there are privacy
implications as big business and government have more tools to conduct surveillance.
Solution providers such as IBM are developing and grouping platforms that ana-
lysts and managers use to minimize risk and improve decision making. For example,
IBM works with such partners as Hortonworks and open source Apache Hadoop to
gather, assess, and present useful data.
The explosion of data requires new methods of analyzing and using information,
including the burgeoning field of artificial intelligence, which relies on the massive
data storage and computing power on internet services hosted by cloud providers.
Drawbacks of Big Data
On The Job . . .
The Challenge of Big Data
“For the first time in human history, we have the ability to col-
lect information, process it, visualize it, and respond to it while
it’s still happening... . We’ve reached a tipping point in history:
today more data is being generated by machines—servers, cell
phones, GPS-enabled cars—than by people. I think Big Data
is going to have a bigger effect on humanity than even the
internet.”
– Rick Smolan
Creator of the Day in the Life series, as he welcomed participants
on October 2, 2012, to the conference The Human Face of Big
Data (retrieved from http://the_human_face_of_bigdata.com)
ARTIFICIAL INTELLIGENCE.
Artificial intelligence (AI), sometimes called “machine
intelligence” imitates such human intelligent behaviours as learning, reasoning, plan-
ning, solving problems, observing, moving, and manipulating objects. AI is used in
vehicles, electronic personal assistants, robots, and thousands of other applications,
including lightning fast data gathering and assessment.
Technology companies such as Adobe, Facebook, Microsoft, and Samsung have
set up in Canada to take advantage of the AI development talent found in Canada’s
major AI research and development centres: Montreal, Toronto, Edmonton, and
Vancouver. In those centres, university researchers and independent R&D hubs have
created many spinoff startups that create viable commercial applications.
One such application is Vancouver’s Novarc firm, which has responded to a world-
wide shortage of skilled welders by developing welding robots that can be employed in
pipeline construction, shipbuilding, and other industrial settings. These robots work in
conjunction with human operators who set and supervise the robot that performs the
manual welding. In essence, the human and the robot collaborate to perform the job.
According to Novarc CEO, Soroush Karimzadeh, “The robot works as a productivity
tool to enhance the capabilities of existing welders and operators with very little train-
ing. That’s different than traditional robots where you replace workers” (Kerr).Benefits of artificial
intelligence
Benefits of Big Data
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