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Data Warehouse & Data Mining
Assignment # 2
Submitted To: Mr. Aamer Hanif
Submitted By: Umair Shahid
(080515)
Adnan Hassan Butt (080453) Amir Jabbar
Date: October 21, 2011
(080531)
Chapter 10
Review Questions
Q#2: Why is the entity-relationship modeling technique not suitable for the data warehouse? How is dimensional modeling different?
Ans:
Q#3: What is the STAR schema? What are the component tables?
Ans:
Q#4: A dimension table is wide; the fact table is deep. Explain.
Ans:
Q#6: Differentiate between fully additive and semiadditive measures.\ Ans:
Q#7: Explain the sparse nature of the data in the fact table. Ans:
Q#8: Describe the composition of the primary keys for the dimension and fact tables.
Ans:
Q#9: Discuss data granularity in a data warehouse.
Ans:
Exercise Question Q#1: Match the columns: 1. information package 2. fact table 3. case tools 4. dimension hierarchies 5. dimension table 6. degenerate dimensions 7. profit margin percentage 8. data granularity 9. STAR schema 10. customer demographics
A. enable drill-down B. reference numbers C. level of detail D. users understand easily E. semi-additive F. STAR schema components G. used for dimensional modeling H. dimension attribute I. contains metrics J. wide
Ans: Q#2: Refer back to the information package given for a hotel chain in Chapter 5 (Figure 5-6). Use this information package and design a STAR schema. Ans:
Q#4: You are the data design specialist on the data warehouse project team for a manufacturing company. Design a STAR schema to track the production quantities. Production quantities are normally analyzed along the business dimensions of product, time, parts used, production facility, and production run. State your assumptions. Ans: Q#5: In a STAR schema to track the shipments for a distribution company, the following dimension tables are found: (1) time, (2) customer ship-to, (3) ship-from, (4) product, (5) type of deal, and (6) mode of shipment. Review these dimensions and list the possible attributes for each of the dimension tables. Also, designate a primary key for each table.
Ans:
Chapter 11 Review Questions Q#1: Describe slowly changing dimensions. What are the three types? Explain each type very briefly. Ans:
Q#2: Compare and contrast Type 2 and Type 3 slowly changing dimensions. Ans:
Q#4: What are junk dimensions? Are they necessary in a data warehouse? Ans:
Q#5: How does a snowflake schema differ from a STAR schema? Name two advantages and two disadvantages of the snowflake schema. Ans:
Q#7: What are aggregate fact tables? Why are they needed? Give an example. Ans:
