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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 2 of 10

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Answer: (b).Correction of errors in source systems Explanation:Type 1 changes in dimension tables primarily involve the correction of errors in source systems.
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Answer: (d).When the change is a correction of an error Explanation:The old value in the source system needs to be preserved in Type 1 changes only when the change is a correction of an error.
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Answer: (b).Overwrite the attribute value in the dimension table row with the new value Explanation:The method for applying Type 1 changes to the data warehouse is to overwrite the attribute value in the dimension table row with the new value.
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Answer: (c).To preserve historical data and track changes over time Explanation:Type 2 changes are applied to dimension tables to preserve historical data and track changes over time.
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Answer: (d).To track orders by state and date Explanation:The essential requirement for implementing Type 2 changes is to be able to track orders by state and date.
Q16.
How are orders for a customer with Type 2 changes in marital status separated in the data warehouse?
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Answer: (d).By using effective date ranges Explanation:Orders for a customer with Type 2 changes in marital status are separated in the data warehouse by using effective date ranges.
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Answer: (a).Overwrite the attribute value in the dimension table row with the new value Explanation:The method for applying Type 2 changes to the data warehouse is to overwrite the attribute value in the dimension table row with the new value.
Q18.
What is the primary nature of Type 3 changes in dimension tables?
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Answer: (c).Tentative or soft revisions Explanation:Type 3 changes in dimension tables are characterized as tentative or soft revisions.
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Answer: (c).To count orders in two ways for a certain period Explanation:Type 3 changes are typically used in data warehousing to count orders in two ways for a certain period, allowing the ability to track forward and backward.
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Answer: (c).To compare performances across transitions Explanation:Type 3 changes in data warehousing are used to compare performances across transitions.

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