Part 1)

Excel is probably the most popular spreadsheet software for PCs. Why? What can we do with this package that makes it so attractive for modeling efforts?

Min 225 words

Part 2)

1. How does prescriptive analytics relate to descriptive and predictive analytics?

2. Explain the differences between static and dynamic models. How can one evolve into the other?

3. What is the difference between an optimistic approach and a pessimistic approach to decision making under assumed uncertainty?

4. Explain why solving problems under uncertainty some- times involves assuming that the problem is to be solved under conditions of risk.

Min 160 words each question. Discussion # must be proceed by the answer.

Part 3)

What are the common business problems addressed by Big Data analytics? In the era of Big Data, are we about to witness the end of data warehousing? Why?

Min 225 words

Part 4)

1. What is Big Data? Why is it important? Where does Big Data come from?

3. What is Big Data analytics? How does it differ from reg- ular analytics?

4. What are the critical success factors for Big Data analytics?

5. What are the big challenges that one should be mind- ful of when considering implementation of Big Data analytics?

Min 160 words each question. Discussion # must be proceed by the answer.


Total 225*2 + 140*8 = 1620 words (round to 1600).

Each part needs to be attached as separate file.

Plagairism report must for each part

APA formatting and each part needs to have at least 2 references.