{"id":48521,"date":"2013-05-02T00:00:00","date_gmt":"2013-05-02T00:00:00","guid":{"rendered":"https:\/\/www.techopedia.com\/video-kate-crawford-of-microsoft-on-big-data-vs-data-with-depth\/"},"modified":"2013-05-02T00:41:47","modified_gmt":"2013-05-02T00:41:47","slug":"video-kate-crawford-of-microsoft-on-big-data-vs-data-with-depth","status":"publish","type":"post","link":"https:\/\/www.techopedia.com\/2\/29294\/trends\/big-data\/video-from-big-data-to-data-with-depth","title":{"rendered":"Video: Kate Crawford of Microsoft on Big Data Vs. Data With Depth"},"content":{"rendered":"

A fascinating presentation by Kate Crawford, principal researcher at Microsoft Research, at the 2013 Strata Conference takes a closer look at big data<\/a> and what it means, exploring some of what Crawford calls "algorithmic illusions" and the limitations of the large-scale data solutions that are being embraced in many parts of the business world.<\/p>\n

Using a fundamental analogy to an optical illusion involving a spinning cat, Crawford makes the case that while big data is essential to many business applications, there\u2019s more than one way to interpret many of the results of data sets that may seem objective to human decision makers.<\/p>\n