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DATA WAREHOUSING FUNDAMENTALS: A Comprehensive Guide for IT Professionals by Paulraj Ponniah

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11.9. EXERCISES

  1. Indicate if true or false:

    1. Type 1 changes for slowly changing dimensions relate to correction of errors.

    2. To apply Type 3 changes of slowly changing dimensions, overwrite the attribute value in the dimension table row with the new value.

    3. Large dimensions usually have multiple hierarchies.

    4. The STAR schema is a normalized version of the snowflake schema.

    5. Aggregates are precalculated summaries.

    6. The percentage of sparsity of the base table tends to be higher than that of aggregate tables.

    7. The fact tables of the STARS in a family share dimension tables.

    8. Core and custom fact tables are useful for companies with several lines of service.

    9. Conforming dimensions is not absolutely necessary in a data warehouse.

    10. A value circle usually needs a family of STARS to support the business.

  2. Assume you are in the insurance business. Find two examples of Type 2 slowly changing dimensions in that business. As an analyst on the project, write the specifications for applying the Type 2 changes to the data warehouse with regard to the two examples.

  3. You are the data design specialist on the data warehouse project team for a retail company. Design a STAR schema to track the sales units and sales dollars with three dimension tables. Explain how you will decide to select and build four two-way aggregates.

  4. the data designer for an international bank, consider the possible types of snapshot and transaction tables. Complete the design with one set of snapshot and transaction tables.

  5. For a manufacturing company, ...

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