Choose one academic/scholarly article or presentation related to the data aspects of information technology

Choose one academic/scholarly article or presentation, related to the data aspects of information technology, particularly business intelligence, data mining, and data analytics, from any relevant academic journal, the Gartner site, or the Teradata site. The journals for the ethics classes would work (Ethics and Information Technology or Computers in Human Behavior.) The journals are available free of charge via the university online library. You can get assistance on how to use the online library by visiting the Student Services tab in the main Blackboard window.

Part 1 Academic topic is attached below.

An APA/MLA/Chicago/etc. reference for the item – basically, let your professor and your classmates know how to find it if we want to read/watch it.

TL;DR

Why you chose this item.

A brief summary of the main points that the author made in the item.

An analysis of the item. Points to address (all 7 of them):

Did the author have a clear purpose for the item? What makes you believe so?

Was this purpose accomplished? How?

Did the author present compelling evidence to support main points?

Does the item have gaps? What sort?

Did the author present the information in a way that readers would find appealing? In what way?

Is the world a better place for this item being written/given? How?

How does this item relate to the real world, either business-wise, or personally? If it doesn’t, state why.

You don’t have to write in a boring and stilted academic style in your summary and analysis – it’s all right (and encouraged!) to write in an engaging style! It’s recommended that you do make a clear distinction between the summary and analysis sections of the paper, if only to remember to address all 7 points of the analysis assignment.

Part 2 Non-Academic Item (Choose a Topic)

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 Technical, 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.