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Requirements for the Summary-Reflection Paper: For each reading article, you are responsible for writing a summary-reflection essay ( around3 pages or more as needed) (after you read it). This essay...

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Requirements for the Summary-Reflection Paper:

For each reading article, you are responsible for writing a summary-reflection essay ( around3 pages or more as needed) (after you read it). This essay should reflect your reflections of the concepts and theoretical frameworks discussed and the confusions you may have.Rather than simply repeat or even copy/paste from original reading materials, please focus on your understanding of the concepts and theoretical frameworks. To be more specific, besides a brief summary, you should have a major section dedicated to the confusions you have with the concepts and models in the reading materials. You should comment on those concepts and models with your own opinions based on working experiences, readings from the library, and reflections of your previous learning.

If you just repeat abstract concepts from the reading materials, you will not earn a high score. You should connect concepts with job/internship experiences.

The following rubrics of essay evaluation could be used to guide your writing. All essays are single-spaced with top and bottom margins of 1 inch and left and right-side margins of 1 inch and the font size should be 12.

Answered Same Day Mar 15, 2021

Solution

Anuja answered on Mar 17 2021
145 Votes
Big Data, Analytics and the path from Insights to Value
- Steve LaVelle, Eric Lesser, Rebecca Shockley, Michael S. Hopkins and Nina Kruschwitz
The world and its businesses are piling up with data, and there is much more we can do than just thrusting it aside and creating trash. According to this study conducted by MIT Sloan Management Review group, with contributions from over 3000 executives, spread across 108 countries, a company’s data definitely has a story to tell. We can undoubtedly state that the best performing companies have been using data analytics to their benefits, in comparison to the lower performing ones. But what we see here in detail is why is there apprehension regarding application of data analytics to convert good data into useful insights. This is when we notice that the problem lies not in lack of knowledge or costs but it is mostly about the management where they feel that in comparison to other priorities of the company to grow, data analytics would actually not be that beneficial. So, the paper suggests a 5-recommendation approach to deal with this problem. The approaches, I feel are very practical in nature because it explains how to deal with the data and get the suitable results. Using small chunks of data to meet an immediate requirement, and to go on adding to this churning of data could be a good start followed by dealing with the ways the data could be generated in a more effective and trustworthy fashion.
Apart from understanding
oadly each and every aspect discussed in the paper and the problems associated with applying those aspects, it is important for us to understand the real world. The most important thing in the present day is the collection of data and its usage. Now, data mining and analytics is very new concept...
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