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Case Study: [Big Data nalysis] The problem is to reduce churn ratio by 5% quarterly by analyzing CDR, credit report and billing data of telecom
Case Study: [Big Data nalysis]
The problem is to reduce churn ratio by 5% quarterly by analyzing CDR, credit report and billing data of telecom operators to mine out churn trends of a specific region or a specific person or and age group.
Questions:
1. How do Privacy and Ethics apply to your problem?
2. What are some of the tricky issues in managing privacy?
3. Describe the difference between human and technical factors
4. How does the Menlo Report adjust the Belmont principles for Big Data research?
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