More Data, More Prob­lems 7 Government Planning Boston’s Mayor Marty Walsh, for instance, uses real-­time data for mea­ sur­ing every­thing from shootings and potholes to building permits and edu- cation issues in order to promote his agenda for the city. Useful dashboards displayed in the mayor’s office show him impor­tant key per­for­mance indica- tors (KPIs) for the last 30 days so he is able to carefully benchmark goals as well as set reasonable expectations for ­ future strategy (Hillenbrand, 2017). Walsh also has an instant glimpse into the vari­ous prob­lems and issues that are the most pressing for this city of nearly 680,000 ­people. News and Media Consumption For good or bad, Big Data often determines what media and news is rec- ommended to ­ people as they browse their newsfeed. For instance, ser­vices such as Twitter and Facebook suggest content mainly based on what is shared or talked about the most. The use of social media is impor­tant not only to determine which news gets the most attention. Journalists, in the reporting stage, often use social media data for reporting a story. They can, for example, use Twitter’s advanced search features for collecting posts from both a specific place and specific time. Sports The 2011 movie Moneyball, starring Brad Pitt and Jonah Hill, was among the first influences that placed mainstream attention on sports ana- lytics. Analytics play an increasingly impor­tant role in many professional sports. Major League Baseball statistics have always been a key part of the game in the United States. Nowadays, much data is made available on sports that librarians can curate and make available to patrons and students inter- ested in sports analytics. Most sport analytics deal with player personnel decisions and roster movements however, ­there is also a business aspect where data scientists can predict ticket pricing and sponsorship return on investment for the most in-­demand games between two popu­lar teams. Big Data and the Data Deluge ­ Today, data is being produced at an unpre­ce­dented rate, spurred on by new technological advancements. First, we must understand where Big Data originates from and what types are available to researchers and society at large. It is impor­tant to note that machine learning, the Internet of ­Things (IoT), and the digitization of health care generate millions of gigabytes ­every second. Reports say data from the U.S. healthcare system alone reached, in 2011, 150 exabytes. At this rate of growth, big data for U.S. healthcare ­ will soon reach the zettabyte (1021 gigabytes) scale and, not long ­after, the yottabyte (1024 gigabytes). (Raghupathi and Raghupathi, 2014, p. 2) ­ Today, besides conventional data sources, ­ there are vari­ous digital data sources such as social media, Google trends, data coming from satellites, among ­others. It is worth mentioning that such large amounts of data
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