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Taming the big data analytics tiger

Big data analytics has potential, but it also needs better governance and training, said data leaders at IBM Information On Demand 2013.

Data in greater volume, velocity and variety has some business leaders riding a big data analytics tiger in search of new commercial opportunities.

Now, several years into the big data era, some taming of the tiger seems to be in order.

That's according to several data professionals from large enterprises on hand at IBM's recent Information On Demand (IOD) conference in Las Vegas.

While they see potential for a new breed of data-driven applications, they also see a need to reign in unbridled efforts, which means applying more rigorous planning, refining analytics skills and instituting more data governance.

"We've seen a huge amount of interest across lines of business, but not a lot of discipline," said R. Madhavan, managing director and chief data scientist at JP Morgan Chase and Co., based in New York.

Speaking to attendees at an IOD panel on big data best practices, Madhavan said he sees risks in big data analytics efforts when people go exploring data without a clear business goal in mind.

We've seen a huge amount of interest … but not a lot of discipline.
R. Madhavanchief data scientist, JP Morgan Chase

There are benefits, though. New apps can provide potential time savings both for data jobs and customer service processes, according to Madhavan. He included archiving, non-analytical applications and data extract, transform, load (ETL) as other possible uses.

Still, Madhaven said he is taking part in efforts to merge dispersed big data undertakings into more cohesive organizational groups in order to improve data governance.

Data variety and 'dangerous insights'

Telecommunications giant Verizon Wireless, also headquartered in New York, has always had data volume and velocity to deal with. What's new is the variety of data that big data analytics must work with, said Ksenija Draskovic, a Verizon predictive analytics and data science manager, who discussed the implications for predictive analytics in another IOD session.

She said implementation of big data analytics is not easy; analytics teams deal with diverse data sets, such as social media feeds, Web logs and call records. These data sources, she said, should not be in "their own islands." Big data, she suggested, can lead analysts astray if they are not careful to study these data sets' interrelationships.

Draskovic warned of ''dangerous insights,'' saying unvetted and suspect findings "can pull an organization apart."

At Verizon, where big data efforts go back several years, Draskovic said her efforts to pair predictive analytics with customer relationship management have reduced "customer churn."

Draskovic said Verizon has continued to work with new data sources that have helped to improve analytics by degrees.

"We noticed that when we stared integrating [social media] comments with traditional structured data, it doesn't turn the world upside down," she said. "But it does add value."

The wider the sources of data, the more important it is to train staff on what it means to not look at just one source and to emphasize that they need to put data findings in context, Draskovic said.

C-suite buy-in of big data kind

Madhavan said he and his JP Morgan Chase colleagues have worked to create better planning methodologies to deal with big data. Steps are in place to ensure business users have an idea beforehand of the kind of data they want to work with, what business goals they hope to achieve, and what kind of revenue can be expected if the new application is wildly successful.

He said well-integrated big data applications can lead to small improvements that in turn drive big value. Using data to reduce customer support calls by just a few seconds improves the user experience and cuts operation costs considerably, he said.

Data managers have to gain top-level sponsorship of big data programs, but they also need to temper business leaders' expectations, Madhavan said.

"These days there is so much coverage of big data. Your CEO and your CFO [chief financial officer] are expecting miracles out of it," he said. "But you should not think of this as a two- or three-year exercise." To succeed, big data programs will require time to grow.

IBM's own research showed there is more ground to be gained in formal executive sponsorship of big data and analytics. In a poll of 900 respondents to the IBM Institute for Business Value's 2013 analytics survey, only 24% of CEOs and chief operating officers (COOs) said they act as lead advocates for using analytics insights in their organizations. That is up 11% from 2012, but it still represents a minority within companies.

Jack Vaughan is SearchDataManagement's news and site editor. Email him at, and follow us on Twitter: @sDataManagement.

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Draskovic said: The wider the sources of data, the more important it is to train staff on what it means to not look at just one source and to emphasize that they need to put data findings in context. After Big Data comes Big Context, right?