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Archive for April 22nd, 2014

 

How Public Organizations Should Treat Big Data

Tuesday, April 22nd, 2014 by

Though the “only human” argument certainly doesn’t apply to Big Data, enterprises and public organizations often expect too much out of the technology. Some executives are frustrated by results that don’t necessarily correlate with their predetermined business plans, and others consider one-time predictive conclusions to beĀ final. The problem is, there’s no guarantee that analytical results will be “right.”

A government-themed action key

A government-themed action key

Public authorities interested in integrating Big Data into their cloud servers need to understand two things. First, digital information possess no political agenda, lacks emotion, and perceives the world in a completely pragmatic manner. And second, data changes as time progresses. For example, just because a county in Maine experienced a particularly rainy Spring doesn’t mean that farming soil will remain moist — future weather conditions may drastically manipulate the environment.

Benefiting from “incorrect” data
If a data analysis program harvests information from one source over the course of 1 hour and then attempts to develop conclusions, the system’s deductions will be correct to the extent that it accurately translated ones and zeroes into actionable intelligence. However, because the place from which the data was aggregated continues to produce new, variable knowledge, it may eventually contradict the original deduction.

Tim Hartford, a contributor to Financial Times, cited Google’s use of predictive analytics tools to chart how many people would be affected by influenza by using algorithms to scrutinize over 50 million search terms. The problem was, 4 years after the project was underway, the company’s system was disenfranchised by the Center for Disease Control and Prevention’s recent aggregation of data, showing that Google’s estimates of the spread of flu-like illnesses were overstated by a 2:1 ratio.

Taking the good with the bad
Although Hartford exemplified Google’s failure as a way of implying that Big Data isn’t what software developers are claiming it to be, Forbes contributor Adam Ozimek noted that the study displayed one of the advantages of the technology: The ability to reject conclusions due to consistently updated information. Furthermore, it’s important to note that Google only collected intelligence from one source, whereas the CDC was amassing data from numerous resources.

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