Mid1_Dw - domains[5 Q.3 What according to you are the...

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Birla Institute of Technology & Science, Pilani Work-Integrated Learning Programmes Division Second Semester 2009-2010 Mid-Semester Test (EC-1 Regular) Course No. : SS ZG515 Course Title : DATA WAREHOUSING Nature of Exam : Closed Book Weightage : 40% Duration : 2 Hours Date of Exam : 06/02/2010 (AN) Note: 1. Please follow all the Instructions to Candidates given on the cover page of the answer book. 2. All parts of a question should be answered consecutively. Each answer should start from a fresh page. 3. Mobile phones and computers of any kind should not be used inside the examination hall. 4. Use of any unfair means will result in severe disciplinary action. Q.1. What are the different kinds of Metadata that exist in a data warehouse? Explain with proper relevant examples. Compare the importance of metadata in a data warehouse to OLTP systems. [5] Q.2. Discuss the need of Data Warehousing in today’s business environment. What are the main problems faced by Data Warehouse professionals in real problem
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Unformatted text preview: domains? [5] Q.3. What, according to you, are the drawbacks of starting a data warehouse project by building data marts? Also explain how Kimball overcame these shortcomings. [5] Q.4. Compare & contrast outriggers & mini-dimensions. Give situations under which you would prefer an outrigger to a mini-dimension & vice versa. [7] Q.5. Explain the entire process of populating and refreshing dimension and fact tables in a data warehouse. First identify the steps involved in chronological order and then give detail of each step involved. Also draw a flow-chart for the same. [10] Q.6. Design star schema(s) to find out products which were on promotion but did not sell. Give an SQL statement for the same. Give an elaborate design of the promotion dimension and also discuss the granularity of your schema(s) in detail. [8] ******** No. of Pages = 1 No. of Questions = 6...
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  • Spring '11
  • raj
  • data warehouse project, Exam Weightage Duration, Data Warehouse professionals, Pilani Work-Integrated Learning

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