Q: List and describe the various situations in which it becomes essential to
List and describe the various situations in which it becomes essential to further normalize dimension tables.
See AnswerQ: Match the following terms and definitions: - periodic data
Match the following terms and definitions: - periodic data - data mart - star schema - data scrubbing - data transformation - grain - reconciled data - dependent data mart - real-time data warehouse -...
See AnswerQ: Explain through common examples why determining grain is critical.
Explain through common examples why determining grain is critical.
See AnswerQ: What are the two situations in which factless fact tables may apply
What are the two situations in which factless fact tables may apply?
See AnswerQ: What is the meaning of the phrase “slowly changing dimension”?
What is the meaning of the phrase “slowly changing dimension”?
See AnswerQ: Why should changes be made to the data warehouse design? What
Why should changes be made to the data warehouse design? What are the changes that need to be accommodated?
See AnswerQ: Briefly explain how the dimensions and facts required for a data mart
Briefly explain how the dimensions and facts required for a data mart are driven by the context for decision making.
See AnswerQ: Martin was very impressed with your project plan and has given you
Martin was very impressed with your project plan and has given you the go-ahead for the project. He also indicates to you that he has e-mails from several key staff members that should help with the d...
See AnswerQ: Explain how data integration is not the only data consolidation technique across
Explain how data integration is not the only data consolidation technique across an enterprise.
See AnswerQ: Describe the current key trends in data warehousing.
Describe the current key trends in data warehousing.
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