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First Steps on the Road to a Big Data Project

When does it make sense to start up a Big Data program? If your email marketing system isn't talking to your sales force automation system, and neither is synched up with your online purchase system, are you really ready to tackle a Big Data project? The answer may surprise you as we examine Big Data and its impact on the next generation digital experience in this sixth, and final, installment of our ongoing series "Are You Ready for Big Data?"

"Start small with Big Data," is the advice from author Bill Franks.

photo of Bill Franks
Bill Franks,

Identify a few relatively simple analytics that won't take much time or data to run.

For example, an online retailer might start by identifying what products each customer viewed within just a few key categories so that the company can send a follow-up offer if they don't purchase.

An organization that is entering the Big Data waters needs simple, intuitive examples to see what the data can do, Franks says, adding that this approach also yields results that are easy to test to see what type of lift the analytics provide.

Next, design a one-off test on some company data: a single month of data from one division for one set of products, for example. Franks cautions against attempting to analyze "all of the data all of the time" when first starting. That can muddy the water with too much data, and lead to high initial costs, a problem that plagues many Big Data initiatives. Instead, utilize only the data you need to perform the initial tests.

At this point, Franks recommends, turn analytic professionals loose on the data. They can create test and control groups to whom they can send the follow-up offers, and then they can help analyze the results. During this process, they'll also learn an awful lot about the data and how to make use of it.

Successful prototypes also make it far easier to get the support required for a larger, more comprehensive effort. Best of all, the full effort will now be less risky because the data is better understood and the value is already partially proven. It's also worthwhile to learn early when the initial analytics aren't as valuable as hoped. It tells you to focus your effort elsewhere before you've wasted many months and a lot of money.

"Pursuing Big Data with small, targeted steps can actually be the fastest, least expensive, and most effective way to go," Franks says. "It enables an organization to prove there's value in a major investment before making it, and to understand better how to make a Big Data program pay off for the long term."

Whatever the size of your initial foray, experts advise to remember that it's a process, a loop. Don't expect fantastic insights the very first time you route two data streams into the same river. Often the benefits don't start to accrue until after you've run your tests through a few iterations.

Even then, because of the newness of the field, Big Data projects—even successful ones—can be frustrating.

photo of Shawndra Hill
Shawndra Hill,
The Wharton School, University of Pennsylvannia

"We still have a ways to go to be able to combine evidence from different types of data sources–for example from text, social networks, and time series data," says Shawndra Hill of the Operations and Information Management Department at The Wharton School of the University of Pennsylvania. "The methods have not caught up yet with the scale and complexities of today’s Big Data."

She adds, "This is both exciting and scary. Exciting because there are a lot of new solutions to be generated, and scary because we are probably leaving a lot of value in databases, and that value may be harder to find as Big Data becomes even bigger data with even more complexity and noise."

Get Started

Analyst Mike Gualtieri, a principal analyst with Forrester Research in Cambridge, Mass., likes to cite a Forrester study that predicts that by 2016, 1 billion people will have smartphones and tablets, "and that number will keep increasing," he says.

photo of Mike Gualtieri
Mike Gualtieri,
Forrester Research

"The more technology people use, the more data they generate, and the more opportunity there is to provide personal experiences," Gualtieri says. "The firms that make things personal will drive things in the future. The others will drop off."

To those who are on the fence, considering a Big Data project, Gualtieri has a simple piece of advice.

"Don't sit this out," he urges. "This is real."

Editor’s Note: This is the sixth, and final, post in the ongoing series “Are You Ready for Big Data?” by DC Denison. Download the complete "Are You Ready for Big Data" ebook to learn more about Big Data, its applications in creating the next generatlon digital experience, and what it takes to get into the game.


Posted on by Karthick (not verified).

In which website i can get good knowledge of big data.... And which tool for bid data is user friendly.....

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