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How companies embark on large-scale analytics initiatives

Rachel Wheeler Archive

If you were anticipating that the business world's reliance on "big data" might soon be exposed as a passing fad, you may be out of luck. On the contrary, companies are now investing more than ever into analytics, as they're eager to capitalize on the wealth of information that's out there.

1to1 Media recently highlighted how massive this trend has become. The news source cited survey results from International Data Corp. showing that the total scope of the "digital universe" should hit 40,000 exabytes - that's 40 trillion billion bytes - by 2020. For perspective, that information would require more than 15.6 million 64 gigabyte iPhones to store.

The catch, though, is that most companies don't know how to use all that data. They've become incredibly active amid all the big-business hype that's out there - they're collecting more information, striving for data quality and trumpeting for greater analytics - but that doesn't mean they're entirely sure of what steps to take in the "big data" process.

IDC forecast in December that the big data technology and services market will see a 27 percent compound annual growth rate through 2017, reaching $32.4 billion - but at the same time, Gartner notes that a whopping 85 percent of Fortune 500 organizations "will be unable to exploit Big Data for competitive advantage" in 2014 or 2015.

"There's a lot of data out there," said Niren Sirohi, vice president of predictive analytics at iKnowtion, according to 1to1. "[Businesses] are stuck in the mindset of collecting and storing big data, not analyzing it."

How, then, can they set out on the fast track to better data analysis? Luckily, there's a four-step process for that.

Strive for multi-channel collection
The first step for many companies who want "big" data on their side is to focus on collecting as much information as possible. Often, this means relying on multiple channels and integrating them seamlessly. Information on customers can be found through consumer care channels, social media interactions, mobile apps, web services and more. If companies can weave together all these sources and build robust banks of data, they're off to a good start.

Break down the client base
An increasingly major focus for many businesses is customer segmentation. Data scientists are eager to break down all the information they have about their client bases into smaller categories, striving to understand individual local areas and demographic groups. This requires very high standards for data quality, as one mistake can lead to an individual being categorized incorrectly, which throws off a company's findings. With accurate information, though, the possibilities are endless.

Gain a local focus
Ron Wince, president and general manager at Peppers and Rogers Group, told 1to1 that "small data" is just as important to his company as big data. Translation: You can learn a lot about improving your operations simply by zooming in and gaining a local focus. The beauty of data collection is that big companies can understand local communities just as well as small mom-and-pop shops in the area. All they need to do is narrow their focus on the places that matter most.

Try to predict the future
One growing trend in the world of big data is predictive analytics. Companies don't just want to understand what's happening in their industry now - they want to use analytical solutions to figure out what will happen in the future, so that they can stay one step ahead of their competitors. This requires building complex models and starting from a very high standard of data quality, but it can be a tremendous business boon if done correctly.

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