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6 Ways To Ask Smarter Questions Of Big Data

To drive more value out of your big data, you have to start with the right questions. Here are six strategies for improving the quality of the questions you ask big data.
Start With A Goal
Understand The Forest And The Trees
Collaborate With Goals In Mind
Take Advantage Of Machine Learning
Align Questions With Data
Don't Skew The Results
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Some organizations are driving more value out of big data than others. They're the ones redefining how businesses interact with their customers. They're the ones using data to transform their business models and to innovate.

Getting there is a matter of maturity, however. It takes a critical mass of data, tools, expertise, and dogged curiosity, as well as a willingness to act on the data. Even then, businesses get varied results.

Asking better questions of data is both an art and a science, and it's an iterative process. The most sophisticated and competitive companies are constantly striving to improve their understanding of what data can tell them, and what they can ask of the data.

[ See how companies are turning social media data into dollars and cents. Read 7 Smart Ways To Leverage Social Data. ]

"Most things don't start and end with a single question," said Fabio Luzzi, VP of advanced analytics and data science at mass media company Viacom. "The quality of your questions gets better along the way."

Many organizations are successfully improving operational efficiencies, but fewer are realizing other types of strategic impact that can make them more competitive.

"It's easy to show ROI by improving operational efficiency, but it's much harder to drive top-line revenue impact on business value," said Olly Downs, chief scientist at big data analytics company Globys. "You want to find something that has a huge impact, and there are capabilities now that allow you to do things that were not possible before."

Here are a few ways to improve the quality of the questions and ultimately the quality of insights and the quality of actions taken.

 
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