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Welcome to the Advanced Topics in Dimensional Modeling MCQs Page

Dive deep into the fascinating world of Advanced Topics in Dimensional Modeling with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Advanced Topics in Dimensional Modeling, a crucial aspect of Data Warehousing and OLAP. In this section, you will encounter a diverse range of MCQs that cover various aspects of Advanced Topics in Dimensional Modeling, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Data Warehousing and OLAP.

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Check out the MCQs below to embark on an enriching journey through Advanced Topics in Dimensional Modeling. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Data Warehousing and OLAP.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Advanced Topics in Dimensional Modeling. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Advanced Topics in Dimensional Modeling MCQs | Page 8 of 10

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Q71.
What is typically shared among the fact tables in a family of STAR schemas?
Discuss
Answer: (c).Dimension tables Explanation:Dimension tables are typically shared among the fact tables in a family of STAR schemas.
Q72.
In what kind of business would it make sense to have families of STAR schemas consisting of transaction and snapshot schemas?
Discuss
Answer: (a).Banking or telephone services Explanation:In businesses like banking or telephone services, it makes sense to have families of STAR schemas consisting of transaction and snapshot schemas.
Q73.
In which type of business does it make sense to have a schema capturing transaction data that supports strategic decision making and revenue analysis?
Discuss
Answer: (d).Telephone companies Explanation:A telephone company benefits from a transaction schema to support strategic decision making and revenue analysis.
Q74.
What kind of data analysis is primarily supported by a transaction schema?
Discuss
Answer: (d).Product sales analysis Explanation:A transaction schema primarily supports data analysis related to individual transactions, such as product sales analysis.
Discuss
Answer: (b).Questions about shifting and movement of account balances Explanation:A snapshot schema typically addresses questions about the shifting and movement of account balances at specific intervals.
Q76.
In a bank's data warehouse, what does the core fact table typically contain?
Discuss
Answer: (a).Metrics common to all types of accounts Explanation:The core fact table in a bank's data warehouse typically contains metrics that are common to all types of accounts.
Discuss
Answer: (c).To contain metrics specific to a particular product or service Explanation:The custom fact tables in a family of STARS hold metrics that are specific to a particular product or service.
Discuss
Answer: (b).Allows for better tracking and analysis of specific products or services Explanation:Core and custom tables allow for better tracking and analysis of specific products or services, which is especially beneficial for businesses with diverse offerings.
Discuss
Answer: (b).Raw materials, assembly, packaging, and distribution Explanation:In a manufacturing business, a product typically travels through steps involving raw materials, assembly, packaging, and distribution before becoming finished goods.
Q80.
What is the primary purpose of creating STAR schemas for different steps in a value chain in a business?
Discuss
Answer: (c).To track important metrics at different steps Explanation:STAR schemas are created to track important metrics at different steps along the value chain in a business.

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