1)      Draw and explain the architecture of on-line analytical mining.

2)      Briefly discuss the data warehouse applications.

3)      What is a data warehouse? Briefly discuss the need for data warehousing?

4)      A data warehouse can be modeled by either star schema or snowflake schema. Briefly describe the similarities and differences of the two models, and then analyze their advantages and disadvantages with regard to one another. Give your opinion of which might be more empirically useful and state the reasons behind your answer.

5)      Compare OLAP systems versus statistical databases.

6)      What is concept hierarchy? Describe the OLAP operation in multidimensional data model.

7)      What is starnet model? With an example, describe the usage of starnet query model for querying multidimensional     database.

8)      Explain three-tier data warehouse architecture.


9)      Explain data warehouse architecture and its implementation.

10)  With an example, describe snowflake and fact constellations.

11)  What is a measure? How measures are computed? Describe the organization of measures.

12)  Differentiate operational database systems and data warehousing.

13)   Describe efficient computation of data cubes.

14)  Describe efficient computation of OLAP queries.

15)  Explain indexing OLAP data.

16)  What is data warehouse? Explain in detail.

17)  Discuss about further development of data cube technology.

18)   What are the schemas for multidimensional databases? Explain with examples.

19)  Explain the implementation of data warehouse.

20)  Discuss about a multidimensional data model in detail with example.

21)   Discuss about various types of warehouse servers for OLAP processing.

Draw the integrated OLAM and OLAP architecture. Explain
4/1/2013 11:53:05 pm

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    March 2012