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Big Data 2013
Sizing Up Big Data, Broadening Beyond the Internet
By Steve Lohr
June 19, 2013 11:09 pm June 19, 2013 11:09 pm (BUTTON)
Photo
HOW WE FEEL A visual representation of recent
sentiment, as expressed on the Internet. Good feelings are brighter;
negative ones are darker.
HOW WE FEEL A visual representation of recent sentiment, as expressed
on the Internet. Good feelings are brighter; negative ones are
darker.Credit
In his young career, Jeffrey Hammerbacher has been a scout on the
frontiers of the data economy.
Big Data 2013
A special section on the business and culture of big data.
In 2005, Mr. Hammerbacher, then a freshly minted Harvard graduate, did
what many math and computing whizzes did. He went to Wall Street as a
“quant,” building math models for complex financial products.
Looking for a better use for his skills, Mr. Hammerbacher departed to
Silicon Valley less than a year later and joined Facebook. He started a
team that began to mine the vast amounts of social network data
Facebook was collecting for insights on how to tweak the service and
target ads. He called himself and his co-workers “data scientists,” a
term that has since become the hottest of job categories.
Facebook was a fabulous petri dish for data science. Yet after two and
a half years, Mr. Hammerbacher decided it was time to move on, beyond
social networks and Internet advertising. He became a founder of
Cloudera, a start-up that makes software tools for data scientists.
Then, starting last summer, Mr. Hammerbacher, who is now 30, embarked
on a very different professional path. He joined the Mount Sinai School
of Medicine in Manhattan as an assistant professor, exploring genetic
and other medical data in search of breakthroughs in disease modeling
and treatment.
The goal, Mr. Hammerbacher said, is “to turn medicine into the land of
the quants.”
Graphic
Big Data Will Get Bigger
The story is the same in one field after another, in science, politics,
crime prevention, public health, sports and industries as varied as
energy and advertising. All are being transformed by data-driven
discovery and decision-making. The pioneering consumer Internet
companies, like Google, Facebook and Amazon, were just the start,
experts say. Today, data tools and techniques are used for tasks as
varied as predicting neighborhood blocks where crimes are most likely
to occur and injecting intelligence into hulking industrial machines,
like electrical power generators.
Big Data is the shorthand label for the phenomenon, which embraces
technology, decision-making and public policy. Supplying the technology
is a fast-growing market, increasing at more than 30 percent a year and
likely to reach $24 billion by 2016, according to a forecast by IDC, a
research firm. All the major technology companies, and a host of
start-ups, are aggressively pursuing the business.
Demand is brisk for people with data skills. The McKinsey Global
Institute, the research arm of the consulting firm, projects that the
United States needs 140,000 to 190,000 more workers with “deep
analytical” expertise and 1.5 million more data-literate managers,
whether retrained or hired, by 2020.
Yet the surveillance potential of Big Data, with every click stream,
physical movement and commercial transaction monitored and analyzed,
would strain the imagination of George Orwell. So what will be
society’s ground rules for the collection and use of data? How do we
weigh the trade-offs involving privacy, commerce and security? Those
issues are just beginning to be addressed. The debate surrounding the
recent disclosure that the National Security Agency has been secretly
stockpiling telephone call logs of Americans and poring through e-mail
and other data from major Internet companies is merely an early round.
Big Data is a vague term, used loosely, if often, these days. But put
simply, the catchall phrase means three things. First, it is a bundle
of technologies. Second, it is a potential revolution in measurement.
And third, it is a point of view, or philosophy, about how decisions
will be — and perhaps should be — made in the future.
The bundle of technologies is partly all the old and new sources of
data — Web pages, browsing habits, sensor signals, social media, GPS
location data from smartphones, genomic information and surveillance
videos. The data surge just keeps rising, doubling in volume every two
years. Just two days of the current global data production, from all
sources — five quintillion bytes (a letter of text equals one byte) —
is about equal to the amount of information created by all the world’s
conversations, ever, according to research at the University of
California, Berkeley.
Yet the importance of the sheer volume of data — and its exponential
growth path — can be overstated. There’s a lot of water in the ocean,
too, but you can’t drink it. Beyond advances in computer processing and
storage, the other essential technology is the clever software to make
sense of all that data. These are largely tools taken from the steadily
evolving world of artificial intelligence, like machine learning.
The increasing volume and variety of data, combined with smart
software, may well open the door to what some people call a revolution
in measurement. This technology, they say, is the digital equivalent of
the telescope or the microscope. Both of those made it possible to see
and measure things as never before — with the telescope, it was the
heavens and new galaxies; with the microscope, it was the mysteries of
life down to the cellular level.
Data-driven insights, experts say, will fuel a shift in the center of
gravity in decision-making. Decisions of all kinds, they say, will
increasingly be made on the basis of data and analysis rather than
experience and intuition — more science and less gut feel. Data, for
example, is an antidote to the human tendency to rely too much on a
single piece of information or what is familiar — what psychologists
call “anchoring bias.”
Big Data, its proponents insist, will be the next big trend in
management. Erik Brynjolfsson, director of the MIT Center for Digital
Business, cites the familiar business truism, “You can’t manage what
you can’t measure.” And as it opens new horizons in measurement, the
modern data era, Mr. Brynjolfsson said, will transform the practice of
management. Big Data, he said, will “replace ideas, paradigms,
organizations and ways of thinking about the world.”
But caveats are in order. Big Data is a descendant of Frederick Winslow
Taylor’s “scientific management” of a century ago. His instruments of
measurement and recording were the stopwatch, clipboard and his eyes.
Taylor and his acolytes used these time-and-motion studies to redesign
work for maximum efficiency.
Yet eventually, the excesses of that approach became apparent and even
satirical grist for the movie “Modern Times” by Charlie Chaplin. And
the enthusiasm for quantitative methods has waxed and waned ever since.
Discrimination by statistical inference is a real risk in the Big Data
world, as some personal data trails suggest a correlation that may be
wrong. David C. Vladeck, a former senior Federal Trade Commission
official and a professor of law at Georgetown University, offers this
example: Imagine spending a few hours looking online for information on
deep fat fryers. You could be looking for a gift for a friend or
researching a report for cooking school. But to a data miner, tracking
your online viewing, this hunt could be read as a telltale sign of an
unhealthy habit — a data-based prediction that could make its way to a
health insurer or potential employer.
And, again, the surveillance potential of Big Data technology, if it
runs amok, is scary.
But all technologies involve trade-offs and risks. In ancient times,
fire could cook your food and keep you warm, but, out of control, could
burn down your hut. Cars pollute the air and cause traffic deaths, but
they have also increased personal mobility and freedom, and stimulated
the development of regional and national markets for goods.
Big Data technology is not fundamentally different. Its advance is
probably inevitable, and the risks seem manageable and the potential
benefits enormous. One glimpse of the potential payoff can be seen at
the Mount Sinai Medical Center, in the work being pursued by the group
Mr. Hammerbacher has joined.
Photo
DATA MAN Jeffrey Hammerbacher studies genetic and
other medical data.
DATA MAN Jeffrey Hammerbacher studies genetic and other medical
data.Credit Fred R. Conrad/The New York Times
The 100-member team at the Icahn Institute for Genomics and Multiscale
Biology is headed by Eric E. Schadt, a leading researcher in genomics
and biomathematics. Dr. Schadt joined Mount Sinai less than two years
ago, lured by ample financing and the promise that his group’s work
would not be research in isolation but part of the medical center in
treating patients.
The genomics revolution is on the cusp of realizing its promise,
according to Dr. Schadt, thanks to the advancing technology of genetic
sequencing and analysis. The government-financed Human Genome Project,
completed in 2003, cost $2.7 billion. Today, whole human genome
sequencing, identifying all three billion chemical units in the human
genetic instruction set, can be done for $3,000. In three years, Dr.
Schadt predicts, the cost will be less than $1,000, and in 5 to 10
years, less than $100, almost like a blood test today.
The technology makes it possible not only to observe life at the
molecular level as never before, but also to explore how the minute
ingredients of biology and the environment influence each other in
individual humans — and personalize treatment. People with similar
genetic traits, Dr. Schadt notes, often have very different health
outcomes. Chronic ailments like cancer, heart disease and Alzheimer’s
are not caused by single genes, he said, but are “complex, networked
disorders.”
The Mount Sinai researchers, Dr. Schadt said, intend to combine genetic
information with the medical histories — weight, age, gender, vital
signs, tobacco use, toxic exposure and other data — to build more
sophisticated models of biology and health outcomes. “We’re trying to
move medicine in the direction of climatology and physics; disciplines
that are far more advanced and mature quantitatively,” he said.
Dr. Schadt recruited Mr. Hammerbacher, an overture that coincided with
Mr. Hammerbacher’s research into where next to best apply his skills.
He describes his career as a matter of “following the smartest people
to find the best problem.” Health care, in his view, is “the best
problem by far,” where his talents could do the most good. At Mount
Sinai, Mr. Hammerbacher said he hoped to learn a lot and assemble a
small group of computing and data experts to help accelerate the
genomic and medical research there.
Mr. Hammerbacher remains the chief scientist of Cloudera and splits his
time between San Francisco and Manhattan.
But he is spending more time in New York these days and just bought an
apartment on the Lower East Side for himself and his wife.
Mr. Hammerbacher has qualms about the Big Data realm he has helped
create, including the surveillance potential of the technology. “What
does it mean,” Mr. Hammerbacher pondered at one point, “to live in an
era where things and people are infinitely observed?” And he
appreciates that there is a lot of truth beyond data. “Just because you
can’t measure it easily doesn’t mean it’s not important,” he observed.
While he is perhaps a qualified enthusiast, Mr. Hammerbacher is a data
believer. He calls data the “intermediate representation of science.”
The genome, he said, is “the quantification of the core of what we
are.”
He says he thinks that medicine, and nearly every other field, will
increasingly fall under the sway of what he calls “the numerical
imagination,” which can be distilled in a question: “What is the story
the data tells us?”
A version of this article appears in print on 06/20/2013, on page F1 of
the NewYork edition with the headline: Sizing Up Big Data.
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Big Data 2013, BigData2013, Computers and the Internet, Research,
Science and Technology, Social Networking (Internet)
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