Reference no: EM133035343
1.How would you go about designing a very large, rapidly changing dimension in a multi-dimensional data warehouse? Describe the design and how it would work along with any potential issues you feel that effect performance?
2.A bank needs to deploy an intelligent system capable of deciding on 3 interest rates for new loan applicants as follows: an interest rate of 6% for "high risk" applicants, 4% for "average risk" applicants, and 3% for "low risk" applicants. Describe the process you would use to design and deploy the system, along with algorithm(s) as well as the related formulas you will use for this project?
3.Principal component analysis (PCA) is an exploratory data analysis that is useful for developing predictive models and for visualizing and summarizing data. Describe where PCA is best applied as well as any potential issues surrounding its use?
4.Suppose a retail business (e.g., Coca-Cola) was interested in monitoring online discussion about their product and their competitor's products. What approach would you take, what tools would you use in this approach, and what sort of insights would you try to extract from the data you obtained?
5.You want to identify communities in a graph. When would you use community detection techniques based on edges, and when would you use data clustering techniques based on similarity measures?
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: 1.How would you go about designing a very large, rapidly changing dimension in a multi-dimensional data warehouse?
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