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Choose one item, related to the data aspects of information technology, particularly business intelligence, data mining, and data analytics, from any worthy (see page 3 for the definition of worthy) edited/QAed online source, such as MIT Technology Review, Wired, Ars Technica, TechDirt, Atlantic, The New York Times, The Washington Post, Christian Science Monitor Passcode, CNET, CIO, Information Week (that is not an exhaustive list), a TED Talk (http://www.ted.com/ – you can also find TED Talks on YouTube) by anyone (e.g. Eli Pariser’s “Beware online ‘filter bubbles’, http://www.ted.com/talks/eli_pariser_beware_online_filter_bubbles), or some of the films from the library’s extensive film collections, Films on Demand, Alexander Street, and Kanopy. Look for their Computer Science & IT collections. An example is “Enterprise Automation: What You Need to Know”, https://bellevue-kanopystreaming-com.ezproxy.bellevue.edu/video/enterprise-automation-what-you-need-know
Compose and submit to the 4 different article reviews – “Summary and Analysis: Non-Academic” thread a structured post (a structured post has an overall introduction, an overall conclusion, and a developed body that flows well – generally at least a few paragraphs – at least 250 words for each article, not including the question text itself), using your own words.