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W
e are a big data analytics, mobile app, real-
time nation. Gartner predicts that by
2015, 4.4 million IT jobs will be generated
to support big data, generating 1.9 million
jobs in the United States. With that point, CIO’s must change their
thought process when it comes to big data. This e-guide, from
SearchCIO.com, explains how big data is impacting today’s IT industry and what CIO’s must do to incorporate big data analytics in
their overall business strategy.
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'BIG DATA' ANALYTICS, NUMBER-CRUNCHING NATION
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Not all "big data" analytics are created equal. Not all real-time data is real or
really matters. Not all killer mobile apps kill. That much can be surmised from
even a cursory review of the digital weapons deployed in this presidential
election, already dubbed the nerdiest in American history. But there can be no
doubt that politics, like everything else, is entering the big data analytics world.
Whether the much-touted mobile app used by 34,000 Romney volunteers
to relay real-time voter counts at the polls turned out to be "nothing short of a
failure," as has been reported and denied, or was a match for the Mobile Pollwatcher app used by the Democratic party to rustle up voters to the polls, I'll
leave to the politico-technocrats to judge. The Election Day mobile apps were
designed to interact with the massive databases and big data analytics tools
relied on by the dueling campaigns. And there's no doubt the data mining tools
and predictive analytics used by Project Orca, the Romney campaign's effort
to turn big data into meaningful action, will be compared to death with those
used by Narwhal, the Obama campaign's massive IT system used to segment
and target voters.
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On the face of it, Orca didn't get its Narwhal. But technology? Technology,
its history-making promise and terrible limitations on full display, loomed
larger than ever on the political battlefields, big data in particular. The power of
leveraging big data -- which requires being able to collect it and analyze it with
the right data model -- was breathtaking in this election, as demonstrated by
the polling done by such pollster nerds as Nate Silver, author of the FiveThirtyEight blog in The New York Times, and Princeton neuroscientist Sam Wang.
Aggregating all the polls' results (which were calculated by collecting and analyzing varying amounts of big data), Silver and Wang and their ilk predicted the
outcome of a political process nearly perfectly. Gut feelings, political persuasion, the timbre of one's voice -- those had nothing to do with the predictions.
The pundit class ignored these big data conclusions at their peril, as one after
another confessed how wrong they were -- a day late. "Politics as usual" is done
with.
Politics, of course, is just realizing what savvy merchants have known for
a long time: Aggregating statistics from many people makes human behavior
predictable. Big data analytics overcomes the uncertainty of the variations
among individuals.
As the power of big data to make accurate political predictions sunk in, I
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was reminded of nothing so much as Glik's, a family-owned business I covered
as a retail reporter in St. Louis years ago. The Gliks have been merchants since
1897. In the modern era, their business had become a chain of 50-some fashion
stores that offered national name-brand clothes in small towns in the Midwest,
some with populations as small as 7,000. Come time for the obligatory story on
Christmas sales and whether merchants would make their numbers that year,
the big retailers would put out their hot picks and predictions for the season.
This was the heyday of the "genius merchant": legends -- like media darling Millard "Mickey" Drexler, then of Gap -- who operated on instinct, who
knew in their gut the right cut of coat or color for the season. When I needed a
bead on the season, I made sure to call Jeff Glik, the son who was running the
Glik's chain at the time. Between trips to New York, Jeff would be poring over
weather data, surveying customers, shopping the competition, on the phone
with managers from Missouri to Michigan, crunching the numbers to get just
the right selection for each of the chain's stores. Way before the rise of the big
data-driven retailer, he was doing his own version of Moneyball.
Politics -- along with everything else -- is catching up with retailers. We
are a big data analytics, mobile app, real-time nation. Don't take my word for
it. Gartner Inc. stirred headlines last month with its prediction that by 2015,
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4.4 million IT jobs will be generated to support big data, generating 1.9 million
jobs in the United States. Every big data-related job here will spawn three jobs
outside of IT, for a total of 6 million U.S. jobs over the next four years. That's
how much stock employers put in big data and in the analytics required for
making information into something that matters. It's a job that will lash together mobile technology, social media and cloud computing. Gartner analyst
Peter Sondergaard tried out the slogan "Nexus of Forces" to describe the "next
age of computing." Everything that rises must converge.
The computers that caught your attention many years ago are having profound impacts on civilization, let alone on your role as CIO in this tornado of
big-data mobile computing. If the presidential election proved nothing else
(and for the record, I believe it proved a great deal), it drives home the point to
CIOs that their job can't be about "technology as usual."
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BIG DATA ERA REQUIRES NEW APPROACH TO INFORMATION GOVERNANCE STRATEGY
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Many organizations have struggled with managing unstructured data -- the often text-heavy, unorganized information that, left unattended, can cause huge
risks and unnecessary storage costs.
As the big data era continues, companies will have to reexamine and adapt
their information governance strategy. By 2018, 25% of progressive organizations will manage all their unstructured data using information governance
and storage management policies, up from less than 1% today, predicts Stamford, Conn.-based consultancy Gartner Inc.
"Once it's created, it's around forever," Gartner Research Director Alan
Dayley said of company data at the Gartner Security and Risk Management
Summit in National Harbor, Md., in June. "We need to do something with it,
and we need to start governing it."
The trouble is, many modern organizations struggle with data governance.
The amount of data floating around the average organization -- much of it
trivial -- makes determining who owns specific data, how long to keep that
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data and who is responsible for managing it a difficult proposition. First and
foremost, organizations must understand exactly what data they have, and the
value of it, Dayley said.
Another cause is data confusion, especially from a regulatory compliance
standpoint.
"We're not clear on regulatory and compliance issues," Dayley said. "We
don't understand what we're supposed to keep, so we keep everything."
Information governance strategy implementation and deployment requires input from across the organization, Dayley said during his Gartner
Summit presentation:
Compliance officers should be consulted to interpret regulatory compli
ance requirements and how long information must be retained according to these regulations. They can also help determine audit schedules.
he legal team has responsibility for assessing information risk and
T
determining a defensible deletion policy.
Business users must understand the current and historical value of data
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and need to be included during the information management policy
development.
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The primary goal of an information governance strategy is to make sure
data supports business priorities effectively and efficiently. Any data that presents very little value, such as transient user communications, early working
copies of files and old data from legacy applications, should be deleted, Dayley
added. Over time, the value goes way down, whereas the cost to continue to
manage it goes way up, he said. You just can't keep keeping everything forever. It's costly on storage; it's costly just trying to filter through all of it and
understand it.
INCORPORATE BIG DATA ANALYTICS
If used strategically, analyzing this big data produces huge benefits, said Vice
President and Gartner Fellow Neil MacDonald during the summit. MacDonald
said that when it comes to information security, organizations often establish
baselines of normal data behavior and look for meaningful deviations.
Giving information more context through big data analytics allows organizations to establish a better understanding of this normal behavior and
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determine meaningful deviations from the baselines.
You have to have a very good idea what normal looks like, then look for
meaningful variations from that to infer malicious intent, MacDonald said.
How do you find a needle in a haystack if you don't know what the needle looks
like?
Difficulties arise when organizations are required to govern content that
they did not create and do not own but may be responsible for -- or find value in.
For example, employee-generated social media data creates potential privacy
risks but can also be very useful to the business from a marketing standpoint.
The cloud is another concern, because it's part of a trend wherein IT has
less and less direct control of the organizational infrastructure, MacDonald
said. As more elements of IT infrastructure go mobile, the tech department
must offset these security concerns with detailed auditing, logging and monitoring of big data activities.
You want visibility to compensate for the lack of direct controls, he said.
If properly managed, breaking down and analyzing big data provides huge
business benefits, he added.
You've got the data; why not leverage it? MacDonald said. Focus on your
objective, which is risk prioritized, actionable insight telling you what to do
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and what to focus on so that you can have the most impact on protecting the
assets of your company.
This won't be easy. The volume of information in the big data era, combined
with new file system technologies, repository formats and nascent programming interfaces, mean that more sophisticated and mature archiving, e-discovery and compliance technologies are not yet available, Dayley said.
As a result, organizations will be forced to manage and govern some of this
content using manual policies and practices versus automated software while
they wait for vendors to catch up, he added. Dayley predicts progressive companies will incorporate policies and products to assist them with automatically
governing their unstructured data.
What these tools do is give you a good visualization of the data and help
companies understand what it is, Dayley said.
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