Reference no: EM132816679
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?
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.
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?
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?