Figures don’t lie,  the old saying, but liars can figure. Put another way, even accurate and honest-in-itself data can be presented in misleading ways to support a less-than-honest result. To protect against data-rich lies, we must learn to understand the limitations of data and how it can be used – even inadvertently – to mislead.

Data May Not Lie - But Liars CanBig Data is not only big, it is incredibly varied, potentially including everything from sensor readings to social media messages. And because it is so big and so varied, it can be overwhelming. Who can argue against the data, especially vast quantities of it?

But as Paul Miller points out in “How to Lie With Data,” at DZone, even data that is formally valid and accurate can be presented in misleading ways. And data users need to be aware of the potential for distortion, so that they are not lulled by data that does not really say what someone may be claiming that it says.

Miller, with a cartography background, notes how maps, seemingly so objective, can be used to make misleading implications. And generations ago a little book called How to Lie with Statistics explored the ways that another objective-seeming type of data can be used in the service of lies.

Maps and statistics are just two small corners in the world of Big Data, and its other corners have their own potential for dishonesty. Which is why data users must learn a certain wariness: Does the data really support what it is purported to say?

Who would lie about data? As always, the lies we need to be most wary of are the ones we are tempted to tell ourselves. Does the data truly support that bold, exciting new marketing strategy? Because it is bold and exciting we want it to be supported by the data – and it is all too easy to organize the data in a way that seems supportive.

Don’t be taken in by sophisticated lies, or even by too much enthusiasm and too little understanding. Let GRT Corporation show you how to understand both the strengths and limitations of Big Data.

Big Data and related technologies – from data warehousing to analytics and business intelligence (BI) – are transforming the business world. Big Data is not simply big: Gartner defines it as “high-volume, high-velocity and high-variety information assets.” Managing these assets to generate the fourth “V” – value – is a challenge. Many excellent solutions are on the market, but they must be matched to specific needs. At GRT Corporation our focus is on providing value to the business customer.

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