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The State of the Big Data Market
Contents
Splunk IPO Energizes
Big Data Market &
Commentary from Don
DeLoach at Infobright
‘Big data’ concept has
grown well between
its diminutive
beginnings
The traditional analytics framework is broken,
according to experts in the business analytics space. Many
say the components of the framework are not well-organized
and exclude important pieces. Its structure (usually depicted
as a pyramid), tends to break the analytics process into
segments, which can fracture business. In this E-Guide, learn
about a big data analytics approach, as well as key vendors’
approaches in the space.
Splunk IPO Energizes Big Data Market & Commentary from
Don DeLoach at Infobright
What Splunk and Infobright have done is to take "what is possible" with
machine-generated data and made it practical. As evidenced by the amazing
success of the Splunk IPO last week, "big data" - as in machine-generated
data - got a big lift.
According to Don DeLoach, CEO of Infobright, it takes him back to the late
'90s when IPOs would double in a matter of hours. I asked Don why he
thought that this was such a big event. He said that it is a data point that
acknowledges the big data market is really coming into its own.
In my conversation with Don, he mentioned that emerging landscapes such
as smart power grids and smart power management systems are indicative
of where the explosion of machine-generated data is going. Don also talked
about his respect for the other vendors in the big data space - including
Splunk and IBM's Smarter Planet - and added that these types of systems
will bring along another huge wave of usage of machine-generated data.
You can get the big picture on big data by reading my interviews with Don
DeLoach of Infobright and Sanjay Mehta of Splunk to get the big picture on
big data. (Clicking on the link for each company will take you to my interviews
as featured on the BeyeNETWORK.)
3. Page 3 of 8 Sponsored by
The State of the Big Data Market
Contents
Splunk IPO Energizes
Big Data Market &
Commentary from Don
DeLoach at Infobright
‘Big data’ concept has
grown well between
its diminutive
beginnings
It's going to be exciting to watch this big data space continue to grow, not
only in size but also in capabilities!
‘Big data’ concept has grown well between its diminutive
beginnings
By Nicole Laskowski, News Editor
The traditional analytics framework is broken, according to Simon Zhang,
director of business analytics at Mountain View, Calif.-based LinkedIn Corp.,
and featured speaker at a recent Big Analytics 2012 event in Boston.
Zhang backed his position with two reasons: First, the components of the
framework are not well-organized and exclude important pieces; second, its
structure -- usually depicted as a pyramid -- tends to break the analytics
process into segments, which can fracture the business.
What is 'big data'?
Big data is a general term used to describe the voluminous amount of
unstructured, semi-structured and textual data being created on a daily basis.
Although big data doesn't refer to any specific quantity, the term is often used
when speaking about multiple terabytes to petabytes of data that
organizations can analyze in search of potentially valuable business insights
and trends.
"LinkedIn came up with a new framework," he said. "It's not a pyramid; it's a
diamond."
The design emphasizes more and easier access to data as well as greater
team unity. Both are seen as important characteristics by Zhang and his
colleagues since they aim to find meaningful patterns in their data. But
LinkedIn, like many companies that sell a data product, is well beyond the
average business, which is still wondering how to take advantage of the
widely discussed yet elusive concepts of "big data" and "data science."
4. Page 4 of 8 Sponsored by
The State of the Big Data Market
Contents
Splunk IPO Energizes
Big Data Market &
Commentary from Don
DeLoach at Infobright
‘Big data’ concept has
grown well between
its diminutive
beginnings
In reality, big data emerged years ago and has since been building
momentum, but the topic exploded onto the scene in 2011. Last year,
Gartner Inc., the research IT group based in Stamford, Conn., included big
data on its annual "Hype Cycle for Emerging Technologies" report for the first
time. And analysts began surveying the big data terrain, focusing much of
their attention on an open source technology called Hadoop.
A year later, the concept of big data can still be a difficult one to grasp. Just
pinning down a definition can turn into a daunting task. But while vendors
and analysts figure out how far to stretch that label, understanding where big
data came from can shed some light on how the industry arrived at this point
-- one that just may push businesses to break with tradition.
Big data's roots
The term "big data" has been around for decades. A Quora posting provides
an example of its usage dating back to 1987. Almost 10 years later, in 1996,
Silicon Graphics International Corp.'s chief scientist, John Mashey, gave a
talk called "Big data and the next wave of 'infrastress.'"
"[Infrastress is] stress on the infrastructure of computing," he said in a 1999
interview with Government Computer News. "It's what happens when
technologies move at different speeds and put stress on the parts that aren't
moving so fast."
In his presentation, Mashey explained that CPUs, memory and disk space
were advancing faster than other aspects of computing, such as bandwidth
and file systems. This disparity can create bottlenecks, instability and force
businesses to find workarounds, he said.
At the time, Mashey typically referred to the big data as the growth in data
volume, pointing to a relatively new data source known as the Internet, and
discussed its impact on storage systems. A few years later, Doug Laney, an
analyst with META Group Inc. (which was acquired by Gartner), added to this
description.
5. Page 5 of 8 Sponsored by
The State of the Big Data Market
Contents
Splunk IPO Energizes
Big Data Market &
Commentary from Don
DeLoach at Infobright
‘Big data’ concept has
grown well between
its diminutive
beginnings
"It wasn't just about growing volumes," Laney said. "Information management
was challenged in a variety of ways."
In his Feb. 2001 commentary, Laney described the complexity of the data
landscape as three-dimensional. The volume of data was on the rise, he
observed, but so was the velocity and the variety of data -- big data's three
V's.
His reference to variety was a way of describing structured data residing in
multiple sources. The challenge here, he said, didn't have to do with the
amount of data in each source, but instead with how to integrate all of the
data together.
Big data's variety has evolved since then to reflect multiple data structures,
which have blossomed at an unprecedented rate. In addition to the typical
structured data businesses are familiar with, text, images, video, audio files
and Web logs have emerged.
Although the initial description has changed, Laney's original observation
remains: Data integration is still difficult.
Breaking the v-v-v-ault
Like Mashey, Laney found the Internet -- particularly the groundswell of e-
commerce -- to be a significant factor in the changing data environment.
"The lower cost of e-channels enables an enterprise to offer its goods or
services to more individuals or trading partners and up to 10 [times] the
quantity of data about an individual transaction may be collected -- thereby
increasing the overall volume of data to be managed," Laney wrote in 2001.
E-commerce created a kind of new reality for marketers and retailers,
according to Peter Fader, co-director of the Wharton customer analytics
initiative at the University of Pennsylvania and professor of marketing.
6. Page 6 of 8 Sponsored by
The State of the Big Data Market
Contents
Splunk IPO Energizes
Big Data Market &
Commentary from Don
DeLoach at Infobright
‘Big data’ concept has
grown well between
its diminutive
beginnings
"We were able to all of a sudden see and track all kinds of behavior that
before was invisible," he said. "And we had the technology to create
databases around it."
The Internet fundamentally changed customer relationship management
(CRM) systems, said Fader. There are parallels between the CRM
movement and big data, according to Fader. Businesses regarded the
additional information as key to gaining deeper knowledge of their
customers. And, thanks to Moore's Law, compute power and storage
became cheaper and more accessible, enabling businesses to keep rather
than discard data.
"We're just naturally hoarders," he said. "And when you find assets that might
be of value -- whether it's arrowheads, real estate, or in this case, data -- we
want to grab it all."
The Internet wasn't the only relatively new, promising source of data;
sensors, which also owe a nod to Moore's Law, were coming into their own in
2001. Together, the two had a major impact on the rate, or velocity, at which
data was being produced, Laney said.
"The frequency of the data that spewed off of devices from point-of-sale
systems to RFID scanners to mobile devices was increasing," he said. "We
realized that current systems didn't have the capacity to load and process
that data within a given window."
Ultimately, businesses are still facing what Mashey described back in 1996
as infrastress: Some technologies are growing more quickly than others. And
businesses may need new technologies if they want to take advantage of the
data they've collected and new data sources.
In fact, these days, analysts tend to believe that the three-V definition of big
data falls short. Gartner, for example, recently released a revised definition of
big data -- one that builds on the expanding variety, velocity and volume
characteristics it originally came up with.
7. Page 7 of 8 Sponsored by
The State of the Big Data Market
Contents
Splunk IPO Energizes
Big Data Market &
Commentary from Don
DeLoach at Infobright
‘Big data’ concept has
grown well between
its diminutive
beginnings
Specifically, Gartner states that big data will require "new forms of
information processing for enhanced insight discovery, decision-making and
process automation."
"To claim that it's just about data growth misses the point," Laney said during
a recent Webinar presentation. "Its usage to help the business perform or
transform is just as -- or more -- important to the definition."
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Contents
Splunk IPO Energizes
Big Data Market &
Commentary from Don
DeLoach at Infobright
‘Big data’ concept has
grown well between
its diminutive
beginnings
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