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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 10 of 10

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Q91.
To apply type 3 changes of slowly changing dimensions, overwrite the attribute value in the dimension table row with the new value.

a.

True

b.

False

c.

May be True or False

d.

Can't say

Discuss
Answer: (b).False Explanation:To apply type 3 changes, new columns are added to the dimension table to store historical values, and the current value is updated.
Q92.
Large dimensions usually have multiple hierarchies.

a.

True

b.

False

c.

May be True or False

d.

Can't say

Discuss
Answer: (a).True Explanation:Large dimensions often have multiple hierarchies to provide various levels of granularity.
Q93.
The STAR schema is a normalized version of the snowflake schema.

a.

True

b.

False

c.

May be True or False

d.

Can't say

Discuss
Answer: (b).False Explanation:The STAR schema is a denormalized version, while the snowflake schema is normalized.
Q94.
Aggregates are precalculated summaries.

a.

True

b.

False

c.

May be True or False

d.

Can't say

Discuss
Answer: (a).True Explanation:Aggregates are precalculated summaries stored in the data warehouse to improve query performance.
Q95.
The percentage of sparsity of the base table tends to be higher than that of aggregate tables.

a.

True

b.

False

c.

May be True or False

d.

Can't say

Discuss
Answer: (b).False Explanation:Aggregate tables are often more sparse than base tables as they store summarized data.
Q96.
The fact tables of the STARS in a family share dimension tables.

a.

True

b.

False

c.

May be True or False

d.

Can't say

Discuss
Answer: (a).True Explanation:Fact tables in a STAR schema share common dimension tables.
Q97.
Core and custom fact tables are useful for companies with several lines of service.

a.

True

b.

False

c.

May be True or False

d.

Can't say

Discuss
Answer: (a).True Explanation:Core and custom fact tables allow flexibility in handling different lines of service in a data warehouse.
Q98.
Conforming dimensions are not absolutely necessary in a data warehouse.

a.

True

b.

False

c.

May be True or False

d.

Can't say

Discuss
Answer: (b).False Explanation:Conforming dimensions are important for consistency and integration across the data warehouse.
Q99.
A value circle usually needs a family of STARS to support the business.

a.

True

b.

False

c.

May be True or False

d.

Can't say

Discuss
Answer: (a).True Explanation:A value circle often requires multiple STAR schemas to provide comprehensive support for the business.
Page 10 of 10

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