Big Data Big Money

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Big Data – Big Money Says It Is A Paradigm
Buster
- Tom Groenfeldt

Big Data is attracting big money — $100
million at Accel Partners, the VC firm.
“Big data is one of the biggest
transformational changes in the data center
and IT landscape,” said Ping Li, a partner at
the VC firm Accel Partners, which is running a
$100 million Big Data fund. “It happens once
in a generation,” he told the audience at a
Churchill Club panel in Silicon Valley.
Gartner predicts that data will grow 800
percent over the next five years and 80
percent of the data will be unstructured.
And just what constitutes Big Data? After
SC2011, the US supercomputing conference in
Seattle in November, Addison Snell, an
industry analyst, blurred the lines a bit in a
podcast with HPCwire.
“There is small Big Data just as there is entry
level high performance computing,” he said.
Someone who has worked in gigabytes and
now has to work in terabytes is dealing with
Big Data, added the CEO of Intersect360. “It’s
relative to the infrastructure you had before.”
It may incorporate complex event processing,
data mining and complex real-time analytics.
Big Data can have many elements — large
files, large volumes and real-time I/O within a
short data life span. Every vendor at SC2011
was talking about big data, agreed Nicole
Hemsoth, editor of Datanami.
Or to put Snell’s observation another way, Big
Data breaks existing systems and ways of
working.
“A lot of people know how to work with
data,” observed Anand Rajaraman, “but now

there is a lot more data so the kinds of things
you can do with it and the way you work with
it can are very different. The founder of
companies which have been acquired by
Amazon and Walmart, Rajaraman is now
senior vice president at Walmart Global ecommerce and co-founder @WalmartLabs,
and a professor at Stanford.
“The tools [for Big Data] are very different.
Many of the fundamental algorithms for
predictive analytics depend crucially on
keeping the data in main memory with a
single CPU to access it. Big Data breaks that
condition. The data can’t all be in memory at
the same time, so it needs to be processed in
a distributed fashion. That requires a new
programming model.”
This can be hard for traditional data users to
understand, He watches students attack Big
Data problems by creating a sample, but that
defeats the value of Big Data with all its
potentially informative outliers.
Businesses are catching on to the promise of
Big Data said Luke Lonergan, chief technology
officer at Greenplum, an analytics company
that was acquired by EMC.
“Every business is looking for ways to get
tighter connection with its customers, to
improve prediction and and move them along
a trajectory. We see a certain urgency around
Big Data.”
Traditional users of Big Data — retail, telecom
and intelligence — are already comfortable
with it, said Lonergan. The next big set of
users are in mobile-social, especially
incorporating geo-location. Some areas have

Analytics Training Institute
A Redwood Associates Learning Initiative

been underserved, such as health care, which
he described as the third rail because it has
been too hard and too slow. But now health
care is experiencing fundamental change
similar to what retail felt when customers
came in armed with smartphones and had
more information than sales people. Patients
are starting to acquire more information and
health care providers are developing more
analytics.

legacy business intelligence and ERP, putting
it on top and calling it Big Data. I think we will
see new applications that are Big Data. We
are just starting to see the seeds as people
recognize the potential of the new platform.
We will see startups that will build new
applications which will break the existing
platforms and start again.”

Big Data is also going to change science, said
Rajaraman.

“Big Data is at a stage where early innovators
are out there.” This is like the early days of ecommerce when pioneers had to figure out
components like fraud and payments, he
added.

“The way science is done has evolved over the
centuries — observation, notebooks and then
you come up with a theory. That was followed
by algorithmic science. Now data analysis is
the fourth paradigm for the new way science
is being done ranging from earth science, to
chemistry to biology and psychology. Science
is about more and more data.”
Big Data is not an American fad — it is a global
phenomenon, said Accel’s Li.
“It’s amazing how global this is. Adoption of
Big Data is happening faster in some emerging
markets where they don’t have to content
with legacy databases.” Instead they are using
open source tools with commodity servers
and storage.
“I think we are in the very early days of
transformation,” Li added. Accel is looking for
companies working in data management and
platforms.

Rajaraman agreed.

“Each of those is now a big company. In Big
Data, each of the new use cases will get
commercialized and become a big company
on its own. Data growth today is faster than
Moore’s law and faster than bandwidth
growth, so we need new ways of organizing
data, new computing and algorithms because
computational power is not keeping up.”
People underestimate the degree to which
this can change their business, said
Greenplum’s Lonergan.
“Those with data science teams begin to
understand; others don’t see how much it can
do. Rather than any single stovepipe, we are
about predicting the future. Some expect they
can buy an application to make Big Data
happen, but it doesn’t work that way.
Businesses should see an explosion of new
activity around the explosion of Big Data.”

“A lot of the applications that ride on top of
these new data platforms have yet to be
invented. Right now users are importing

Source:Forbes.com
(http://www.forbes.com/sites/tomgroenfeldt/2012/01/06/big-data-big-money-says-it-is-aparadigm-buster/)

Analytics Training Institute
A Redwood Associates Learning Initiative

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