Chapter 3 Achieving Organizational Alignment for Big Data Analytics

Please answer the following Questions

1. For each of your organizations business functions, identify one or two potential business champions/evangelists for big data.
2. Using what you have learned through discussions with key stakeholders, come up with three elevator pitch sentences describing the expectation for value for big data in fifteen seconds or less.
3. Have you adequately identified the skill sets necessary for evaluating big data technology? List the key skills and capabilities and identify individuals within the organization who currently have some experience with those skills.
4. If there is a skills gap, what are your three key sources for climbing the learning curve?
5. Provide an argument for ripping out the entire data warehouse infrastructure and replacing it with big data.
6. Provide an argument for dovetailing big data as just one component of the existing business intelligence, reporting, and analytics infrastructure.

Chapter 4: Developing a Strategy for Integrating Big Data Analytics into the Enterprise

Please answer the following Questions

1. Recall three experiences with evaluating and adopting new technologies. What were the most valuable lessons learned regarding the successful implementation?
2. What lessons might be relevant to the implementation of a big data solution in your environment?
3. What would you have done differently?
4. Over time, did the new technologies deliver on the original promise?
5. At which point during a technology evaluation did you engage the business users? Was that the right time? Why?

Chapter 5: Data Governance for Big Data Analytics: Considerations for Data Policies and Processes

Please answer the following Questions

1. What are the three most critical dimensions of data quality your business data consumers care about for analytics? Why?
2. How would you specify methods for measuring compliance with the consumers expectations?
3. What are some frequently used reference datasets (such as countries, states, currencies) that would be useful to standardize?
4. Document the data flow for five acquired datasets from entry to the organization to presentation of analytical results. What is the average number of times each dataset is used?
5. Look at five analytical applications and characterize the need for data correction and enhancement based on the need for accuracy and precision.