adplus-dvertising

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.

frame-decoration

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 7 of 10

Explore more Topics under Data Warehousing and OLAP

Q61.
What is the primary consideration when determining an aggregation strategy for a data warehouse?

a.

Reducing the number of dimensions

b.

Achieving a high degree of data normalization

c.

Improving data warehouse performance

d.

Enhancing data loading performance

Discuss
Answer: (c).Improving data warehouse performance Explanation:The primary consideration when determining an aggregation strategy is to improve data warehouse performance.
Q62.
When creating aggregate tables, what can be the effect of the failure of sparsity?

a.

It reduces the number of rows in aggregate tables.

b.

It has no impact on the number of rows in aggregate tables.

c.

It may increase or decrease the number of rows in aggregate tables.

d.

It significantly increases the number of rows in aggregate tables.

Discuss
Answer: (c).It may increase or decrease the number of rows in aggregate tables. Explanation:The failure of sparsity may either increase or decrease the number of rows in aggregate tables, depending on the nature of the data.
Q63.
What is a practical goal for designing aggregation strategies in a data warehouse environment?

a.

Creating as many aggregates as possible to accommodate all user needs

b.

Keeping aggregates visible to end-users for direct access

c.

Reducing storage usage by minimizing the number of aggregates

d.

Focusing exclusively on power users' requirements

Discuss
Answer: (c).Reducing storage usage by minimizing the number of aggregates Explanation:A practical goal for designing aggregation strategies is to reduce storage usage by minimizing the number of aggregates.
Q64.
What should you consider when determining the attributes and combinations for aggregation?

a.

The number of dimensions in the data warehouse

b.

The levels of hierarchies in each dimension

c.

The need to create derived dimensions for every attribute

d.

The technical capabilities of the query tool

Discuss
Answer: (b).The levels of hierarchies in each dimension Explanation:When determining attributes and combinations for aggregation, it's important to consider the levels of hierarchies in each dimension.
Q65.
How does the number of values for an attribute affect its suitability for aggregation?

a.

Attributes with more values are strong candidates for aggregation.

b.

Attributes with fewer values are strong candidates for aggregation.

c.

The number of values for an attribute does not impact aggregation suitability.

d.

All attributes are equally suitable for aggregation.

Discuss
Answer: (b).Attributes with fewer values are strong candidates for aggregation. Explanation:Attributes with fewer values are stronger candidates for aggregation, as they can lead to more effective aggregations.
Q66.
In a hotel chain schema, if the "city" attribute has 25,000 values and "hotel" has 15,000 values, what is the recommendation regarding aggregation?

a.

Aggregate by "city" due to its lower number of values.

b.

Aggregate by "hotel" due to its higher number of values.

c.

Do not aggregate by either "city" or "hotel."

d.

Aggregate by both "city" and "hotel."

Discuss
Answer: (c).Do not aggregate by either "city" or "hotel." Explanation:In this scenario, there is no clear advantage to aggregating by "city" or "hotel" due to the large number of values for both attributes.
Q67.
What is the primary goal of aggregation in a data warehouse environment?

a.

To create as many aggregate tables as possible

b.

To reduce storage usage by minimizing the number of aggregates

c.

To make aggregates visible to end-users

d.

To focus exclusively on power users' requirements

Discuss
Answer: (b).To reduce storage usage by minimizing the number of aggregates Explanation:The primary goal of aggregation is to reduce storage usage by minimizing the number of aggregates.
Q68.
What is a practical approach when designing aggregation strategies in a data warehouse?

a.

Create a large number of aggregate tables initially.

b.

Continuously adjust and revise aggregates based on evolving user needs.

c.

Keep aggregates hidden from end-users.

d.

Focus exclusively on deriving new dimensions for the aggregates.

Discuss
Answer: (b).Continuously adjust and revise aggregates based on evolving user needs. Explanation:A practical approach to designing aggregation strategies involves continuously adjusting and revising aggregates based on evolving user needs.
Q69.
What drives the need for summarization and aggregation in a data warehouse?

a.

Increasing the number of dimensions in the data warehouse

b.

The desire to make aggregates visible to end-users

c.

Improved query performance

d.

Focusing on accommodating power users' requirements

Discuss
Answer: (c).Improved query performance Explanation:The need for summarization and aggregation is primarily driven by the desire to improve query performance.
Q70.
What does a family of STAR schemas consist of?

a.

Multiple STAR schemas with unrelated dimension tables

b.

A collection of STAR schemas serving various purposes

c.

A single STAR schema with multiple fact tables

d.

A set of aggregate fact tables and no dimension tables

Discuss
Answer: (b).A collection of STAR schemas serving various purposes Explanation:A family of STAR schemas consists of a collection of STAR schemas serving various purposes.
Page 7 of 10

Suggested Topics

Are you eager to expand your knowledge beyond Data Warehousing and OLAP? We've curated a selection of related categories that you might find intriguing.

Click on the categories below to discover a wealth of MCQs and enrich your understanding of Computer Science. Happy exploring!

Systems Analysis and Design Methods

Get familiar with the process of designing and improving business systems with our...

MySQL Database

Enhance your knowledge of relational databases with our MySQL MCQs. Understand...

Human Computer Interaction

Enhance your knowledge of Human-Computer Interaction with our specialized MCQs....

Operating System

Dive deep into the core of computers with our Operating System MCQs. Learn about...

Cloud Computing

Stay on top of the biggest trend in IT with our Cloud Computing MCQs. These questions...

Digital Image Processing (DIP)

Delve into the techniques of enhancing digital images with our Digital Image...

MongoDB

Learn the leading NoSQL database with our MongoDB MCQs. Understand everything from...

Digital Logic Design

Understand the foundation of digital computers with our Digital Logic Design MCQs....

Neural Networks

Dive into the world of Artificial Intelligence with our Neural Networks MCQs. Uncover...