mardi 18 février 2014

10 big myths about Big Data

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By Maria Korolov, Network World 
January 27, 2014 06:45 AM ET

Network World - Big Data has dominated tech news of late. It has been touted as a possible solution for everything from intrusion detection to fraud prevention to curing cancer and setting optimal product prices.
But Big Data, which we’re defining as data collected in large volumes, at high velocity and in a variety of formats, isn't a cure-all for every problem. In fact, if companies that believe in some of the myths surrounding Big Data, could head off in the wrong direction, waste a lot of time and money, cost a company its competitive position in the market, or damage a company's reputation.
Here are some of the biggest myths surrounding Big Data.
MYTH 1: Only data scientists can deal with Big Data
In fact, data scientists by themselves are not enough.
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“Data scientists by themselves aren't going to be able to pull off getting the information out of Big Data if you don't know what you're looking for in the first place,” says Pat Farrell, senior director of data analytics at Penn Medicine. “You need people who are familiar with the industry, the domain of knowledge, understand what kind of questions are out there, what insight would be valuable to your particular industry.”
Penn Medicine, for example, includes both a health system and a school of medicine. For a long time, the health system has been collecting clinical data in a data warehouse. Meanwhile, in the school of medicine, new technology is allowing for the sequencing of human genomes, which entails a huge amount of data.
“We know there's value in there somewhere, and we finally have the computing power to access it,” says Farrell. Combining data analytics with expertise in medicine opens up a brand new field of predictive healthcare, he says.
MYTH 2: The bigger the data, the bigger the value
It takes time and resources to collect data, house it, and catalog it, says Farrell. Indiscriminately collecting large masses of data can divert those resources from more worthy projects.
Farrell recommends that companies have a clear idea of the specific metric or key performance indicator that they're looking for before they start collecting data.
“You want to get to the point where you have a handful of nuggets of wisdom that are valuable to you,” he says. “The data by itself, sitting there, is not enough.”
MYTH 3: Big Data is for big companies
Large companies may have more internal sources of data, but even small firms can take advantage of data coming in from social media platforms, government agencies, and data vendors.
“Regardless of the size of your organization, it’s better to make decisions based on data than to simply rely on intuition or gut feelings,” says Darin Bartik, executive director of product management for Dell Software’s Information Management Solutions.
Smaller companies may make data-driven decisions less often than their bigger counterparts, he says, but, when they do, they can make course corrections faster.
“Smaller companies can use best practices to be more data-driven and actually outpace or outmaneuver bigger, slower competitors,” he says.

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