Editor’s Note: Rising Above the Flood of Data
Companies are dealing with a deluge of data, but only necessary data should be collected and, importantly, it needs to be analyzed in order to be useful.
Interestingly, data science that encompasses predictive models is disrupting the conventional location decision process. Those charged with choosing the next site for their facility collect data about labor, real estate, and utility costs as well as taxes and infrastructure. But now they can even utilize data to determine their company’s cultural fit in a prospective location. Data about a location’s lifestyle trends — i.e., residential developments, hotels, restaurants, shopping venues, cultural events, and more — as well as from social media sites can be used to determine how well a company will “fit” into a particular community now and, importantly, in the future. To find out more, read this month’s “Big Data” cover story.
However, can companies actually collect too much data? That’s the suggestion of a recent IndustryWeek article. For example, the IIoT (Industrial Internet of Things) has automated data collection on the shop floor and reduced its costs. Nonetheless, the collection of data requires hardware and software along with maintenance of these conduits. And storing all the collected data is another added expense. Only necessary data should be collected, and the bottom line is it needs to be analyzed in order to be useful. Let’s not forget that “the goal is to turn data into information, and information into insight,” according to Carly Fiorina, the former CEO of Hewlett-Packard Co.
It’s also important to note that increased cybersecurity goes hand-in-hand with the collection of data. Businesses need to protect the vast amounts of data they are collecting because just as big data analytics presents them with enhanced business intelligence, it also enhances opportunities for cybercriminals. Luckily, though, the collection and analysis of data about incidents of cybercrime are helping to thwart these very activities.
It seems big data is being used everywhere — in manufacturing, logistics, financial services, medicine/healthcare, social media and beyond. Whether we like it or not, we cannot staunch the flood of data.
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