Reading report about big data

Sep 13th, 2014
Price: $65 USD

Question description

BUAL 5650/6650/6656

Reading Report #1 – 10% of total grade

Please type the answers using a 12 point font, double spaced, and no less than a 1.25” margin. Make sure your page size is 8.5” x 11” and put your name and your section (ISMN 5650, 6650, or 6656) on the top of the exam. This report should be between 5 and 7 double spaced pages. Be sure to check your answers not only for completeness, but also for structure, grammar, and spelling. Although you are free to use any material to help you when answering the questions, please note that you must correctly cite your sources. Failure to do so may raise the question of plagiarism. Readings other than those from the book(s) are posted on Canvas.

This reading report is based on too BIG to IGNORE chapters 2 and 3, Data Science and its Relationship to Big Data and Data-Driven Decision Making, and the Big Data Executive Survey. The chapters in TBTI speak to the big data revolution and some of the applicable techniques. The data science article explores whether “data science” is part of the picture as required by organizations. The organizations themselves are represented in the executive survey reading.

Develop a well-supported argument that either supports or refutes the idea that organizations must hire data scientists in order to accomplish what is necessary to reap rewards from big data. Although it is OK to quote from or refer to the four readings, do not simply restate what the authors have written. I want to see independent thought on the subject as you will likely be exposed to this debate as you engage in interviews or with colleagues in organizations.

Examples of some of the things you might address would include what data science is, whether the techniques are appropriate for the average end user, whether organizations (as per the survey) appear to agree with the similarities or differences between data science and big data, whether organizations are ready for any of the techniques that are required to benefit from big data, etc.

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