Unformatted text preview:  Q.3 Design a data mart for storing and analyzing Alumni Data of BITS. Give the analysis requirements first. Give example of some analysis queries that can be answered using your schema. Also give some example tuples for all the tables in your schema. And suggest partitioning and aggregation strategies. Did the phenomenon of sparsity failure occur while creating aggregates?  Q.4 What are the advantages and disadvantages of having finest granularity data in the data warehouse?  Q.5 Explain why we go for normalization in designing operational systems and why we avoid it in designing data warehousing systems.  Q.6 Some information that is essential for an operational system but is not required in a data warehouse system. Give examples.  ********** No. of Pages = 1 No. of Questions = 6...
View Full Document
- Spring '11
- data warehouse data, Pilani Distance Learning, Course Title Nature, Exam Weightage Duration, finest granularity data