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Welcome to the The Physical Design Process MCQs Page

Dive deep into the fascinating world of The Physical Design Process with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of The Physical Design Process, a crucial aspect of Data Warehousing and OLAP. In this section, you will encounter a diverse range of MCQs that cover various aspects of The Physical Design Process, 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 The Physical Design Process. 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 The Physical Design Process. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

The Physical Design Process MCQs | Page 8 of 9

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Q71.
How does data clustering improve query performance in a data warehouse?

a.

By eliminating the need for indexing

b.

By accelerating the loading of large tables

c.

By fostering sequential prefetch of related data

d.

By simplifying the process of regular purging

Discuss
Answer: (c).By fostering sequential prefetch of related data Explanation:Data clustering improves query performance in a data warehouse by fostering sequential prefetch of related data.
Q72.
What is a potential advantage of taking an entire partition off-line for maintenance?

a.

Faster index building

b.

Reduced downtime during data corruption

c.

Simplified process of regular purging

d.

Sequential access of related data

Discuss
Answer: (b).Reduced downtime during data corruption Explanation:A potential advantage of taking an entire partition off-line for maintenance is reduced downtime during data corruption.
Q73.
How does parallel processing contribute to performance improvement in a data warehouse?

a.

By eliminating the need for indexing

b.

By fostering sequential prefetch of related data

c.

By splitting processing into components and executing them concurrently

d.

By physically placing related tables close to each other in storage

Discuss
Answer: (c).By splitting processing into components and executing them concurrently Explanation:Parallel processing contributes to performance improvement in a data warehouse by splitting processing into components and executing them concurrently.
Q74.
What is a consideration when applying parallel processing techniques in conjunction with data partitioning?

a.

Placing two partitions on the same storage device for parallel processing

b.

Reducing the number of partitions to simplify processing

c.

Avoiding the use of summary levels in conjunction with parallel processing

d.

Disabling data partitioning to improve parallel processing efficiency

Discuss
Answer: (a).Placing two partitions on the same storage device for parallel processing Explanation:When applying parallel processing techniques in conjunction with data partitioning, a consideration is placing two partitions on the same storage device if they need to be processed in parallel.
Q75.
Why is it important to carefully choose summary and detail levels in a data warehouse?

a.

To eliminate the need for referential integrity checks

b.

To simplify the process of regular purging

c.

To optimize input – output operations based on user requirements

d.

To reduce the downtime during data corruption

Discuss
Answer: (c).To optimize input – output operations based on user requirements Explanation:It is important to carefully choose summary and detail levels in a data warehouse to optimize input – output operations based on user requirements.
Q76.
What is a rolling summary structure in a data warehouse?

a.

Automatically summarizing data based on predefined rules

b.

Summarizing data using bitmapped indexing

c.

Summarizing data based on partitioning

d.

Automatically rolling data to the next higher levels with the passage of time

Discuss
Answer: (d).Automatically rolling data to the next higher levels with the passage of time Explanation:A rolling summary structure in a data warehouse involves automatically rolling data to the next higher levels with the passage of time.
Q77.
How does turning off referential integrity verification during data loading impact performance?

a.

It accelerates the loading of large tables.

b.

It fosters sequential prefetch of related data.

c.

It ensures the validity between two related tables.

d.

It reduces the need for backup and recovery.

Discuss
Answer: (a).It accelerates the loading of large tables. Explanation:Turning off referential integrity verification during data loading accelerates the loading of large tables and improves performance.
Q78.
Why is it important to carefully set the maximum number of concurrent users in a database system?

a.

To ensure data normalization

b.

To prevent data clustering

c.

To avoid bottlenecks and resource consumption issues

d.

To enable data partitioning

Discuss
Answer: (c).To avoid bottlenecks and resource consumption issues Explanation:It is important to carefully set the maximum number of concurrent users in a database system to avoid bottlenecks and resource consumption issues.
Q79.
What is the purpose of setting the checkpoint frequency in a database system appropriately?

a.

To foster data normalization

b.

To minimize the use of system resources

c.

To improve recovery in case of failures

d.

To facilitate data clustering

Discuss
Answer: (c).To improve recovery in case of failures Explanation:The purpose of setting the checkpoint frequency appropriately in a database system is to improve recovery in case of failures.
Q80.
In the context of a financial data mart, how can the use of data arrays contribute to performance improvement?

a.

By fostering data normalization

b.

By preventing the violation of normalization principles

c.

By facilitating the storage of monthly balances in a time series

d.

By avoiding the use of RAID technology

Discuss
Answer: (c).By facilitating the storage of monthly balances in a time series Explanation:The use of data arrays in a financial data mart can contribute to performance improvement by facilitating the storage of monthly balances in a time series.
Page 8 of 9

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