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Without authenticity and quality, big data strategies can fall apart

Big data can generate highly valuable information, but it can also lead to huge mistakes if data quality is lacking. Dave Hendricks recently wrote an article for ClickZ, in which he discussed his experience at this year's IAB Annual Leadership Meeting, a conference revolved around the analytics strategy. Hendricks reports that humorously enough, the majority of the data-savvy attendees used their gut instincts rather than fact-driven insights when packing their bags for the meeting in Phoenix. 

Memory served that it was warm in Arizona this time of year, but attendees found it was unseasonably cold, he reports. And it wasn't just participants; presenters like Google also neglected to check their analytics - or computers - for information. As such, the internet search giant's outdoor tiki-bar-themed booth that was meant to hold a demonstration of its new Chromebook went largely unvisited. 

This an example of what can go wrong when companies don't check information for authenticity, according to Wired Magazine. In this instance, individuals neglected to verify their intuition with existing data, but companies can also run into problems if they don't confirm the accuracy of the information they're using in their big data strategies before acting upon it. 

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