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Mining for Big Value in Big Data
December 11, 2015 Blog

Nate Silver knows a thing or two about the value of Big Data. He famously predicted who would win 49 out of 50 states in the 2008 US Presidential election and the following year was named by Time one of  The World’s 100 Most Influential People. Silver’s Five Thirty Eight site focuses on “data journalism.”

But Silver warned in a recent keynote at the Rich Data Summit that Big Data can be misunderstood and oversold. A popular notion, Silver said, is that “you get your data, you press a button and all of a sudden you have extremely valuable output. This idea is very wrong and dangerous.”

In fact, the work data scientists do is far more complex. “Data scientists aren’t interested in data for data’s sake, we’re interested in relationships,” he said.

Jenny Dearborn, author of the book Data Driven: How Performance Analytics Delivers Extraordinary Sales Results, says we are a tipping point in our ability to collect, manipulate, analyse and act on big data.

“We finally have the ability to manipulate all this data we’ve been collecting and understand what to do with it,” says Dearborn, Chief Learning Officer at SAP.

“We certainly had the information before, but it was hard to access and compile and get a big picture view of it; it was very much nose to the tree. Now we can see the forest and patterns and trends and ‘what does all this mean?’

“With all this information we can for the first time really answer some very big strategic questions: ‘What is the business problem we’re trying to solve?’  ‘What are the big trends here’?’” says Dearborn.

But she agrees with Silver there is no magic button to realising the benefits of Big Data.

“It’s challenging, because it’s not just having the data, but knowing what to do with it,” says Dearborn.

“Knowing what questions to ask, what business problems you are trying to solve and how do you apply analytics to the data you have to answer those big questions. There’s a lot of big strategic thinking that needs to happen in front of looking at your stacks of data or all your reports, and sometimes companies don’t take the time to ask those big questions.

Some Big Data insights are relatively straightforward. Coca Cola has leveraged results from its network of Freestyle drink dispensers to create a new flavour. Freestyle, a kind of drink factory in a touchscreen box, lets customer mix and match over 170 brands of beverages at fast-food outlets, movie theaters and elsewhere.

The soft drink giant is able to collect and analyse all those choices. When it saw a pattern of customers mixing Cherry and Vanilla Coke flavours, voila, it created a new, instantly popular flavour, Coke Cherry Vanilla.

Analyst Doug Henschen at Constellation Research points to manufacturing companies like GE and John Deere who are using Big Data to anticipate when parts are going to need to be fixed, resulting in savings on inventory and maintenance costs.

Henschen’s advice for companies considering investment in Big Data is that it’s okay to be innovative but “start with the business challenges you have today, don’t try and boil the ocean.”

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