In a recent New York Times article, Steve Lohr discusses the growing need for data-literate employees in almost every sector as businesses “drift towards data-driven discovery and decision making” and we move forward in “the Age of Big Data." Lohr refers to a report published last year by McKinsey Global Institute, which projects that “the United States needs 140,000 to 190,000 more workers with ‘deep analytical’ expertise and 1.5 million more data-literate managers.” According to Lohr, the amount of data increases by 50% every year and it is this growing abundance of information that has helped bring us to this so-called Age of Big Data. This rapid data growth can be attributed to things ranging from the creation of new digital sensors by manufacturing firms to greater accessibility to U.S. government data on the internet. According to Lohr, this wealth of new data - in particular, Google searches, Facebook posts and tweets - allow us to observe and measure things in a way that we have previously not been able to do. For example, trends in the number of housing-related searches have more accurately predicted housing sales than real estate economists and a spike in google searches related to flu symptoms tends to precede an increase in flu patients coming to hospital emergency rooms in the region by a couple of weeks. Lohr predicts that business will increasingly rely on analysis of data such as this in decision making as part of “data-guided management”. For example, large retailers such as Walmart and Kohl’s now use data ranging from sales to the weather to time price markdowns.