Explain what MapReduce is and how it is used. Is this still current and appropriate advice?
Please answer every question. No cover page, 2-3 pages, APA format.
1. What updates would you recommend related to Figures 6 & 7 in Chapter 3 (see attached)? Why? Explain.
2. Are there new solutions that are not included in Figures 6 & 7 in Chapter 3 (see attached)? Explain.
3. Would you recommend using a Hadoop cluster? Why or why not?
4. What does your textbook recommend for online analytical processing (OLAP), such as “report the sales of all stores by region and by quarter and compare these figures to last year’s figures”? Explain how it works and the advantages of using it. Is this still the best advice?
5. Explain what MapReduce is and how it is used. Is this still current and appropriate advice?
6. Why would you recommend moving the algorithm to the data rather than the data to the algorithm? Explain the most current products to help you do this. Explain the benefits of in-database machine learning.
7. What would recommend as the best approach (and products) that integrate data from several sources? Explain.
8. What is an Analytics Base Table? How is it used? Why is it important?
9. Finally, the organization wants to know if there are possible legal, ethical, and even biblical viewpoints of concern to the use of the organization’s customer data. What would you recommend to them?