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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 7 of 9

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Q61.
What is a disadvantage of bitmapped indexes?

a.

They require less space compared to B-Tree indexes

b.

They are suitable for high-selectivity columns

c.

They do not need table access after index access

d.

They need reconstruction when new values are introduced for the indexed columns

Discuss
Answer: (d).They need reconstruction when new values are introduced for the indexed columns Explanation:A disadvantage of bitmapped indexes is that they need reconstruction when new values are introduced for the indexed columns.
Q62.
In a data warehouse environment, when are bitmapped indexes more suitable than B-Tree indexes?

a.

When the data warehouse deals with small volumes of data

b.

When the queries involve high-selectivity columns

c.

When analysis involves "what-if" scenarios with multiple predicates

d.

When data tables require frequent updates

Discuss
Answer: (c).When analysis involves "what-if" scenarios with multiple predicates Explanation:Bitmapped indexes are more suitable in a data warehouse environment when analysis involves "what-if" scenarios with multiple predicates.
Q63.
What is a recommended indexing strategy for dimension tables in a data warehouse?

a.

Create a B-Tree index only on the columns used in join conditions

b.

Create a bitmapped index on the primary key column

c.

Create a unique B-Tree index on the single-column primary key

d.

Avoid indexing dimension tables to prevent performance issues

Discuss
Answer: (c).Create a unique B-Tree index on the single-column primary key Explanation:A recommended indexing strategy for dimension tables in a data warehouse is to create a unique B-Tree index on the single-column primary key.
Q64.
When considering multicolumn indexes for dimension tables, what should be considered for arranging columns?

a.

Arrange columns based on alphabetical order

b.

Arrange columns randomly

c.

Place the columns more frequently accessed or at higher hierarchical levels at the high order

d.

Place the columns with low selectivity at the high order

Discuss
Answer: (c).Place the columns more frequently accessed or at higher hierarchical levels at the high order Explanation:When considering multicolumn indexes for dimension tables, it's advisable to place the columns that are more frequently accessed or at higher hierarchical levels at the high order of the multicolumn indexes.
Q65.
Which technique enables more data to be loaded into a single block, improving data retrieval performance?

a.

Data partitioning

b.

Table merging

c.

Regular purging of data

d.

Physical data compacting

Discuss
Answer: (d).Physical data compacting Explanation:Physical data compacting enables more data to be loaded into a single block, improving data retrieval performance.
Q66.
What is a key advantage of data partitioning in a data warehouse?

a.

Reducing the need for backup and recovery

b.

Eliminating the need for indexing

c.

Accelerating the loading of large tables

d.

Simplifying the process of purging and archiving records

Discuss
Answer: (c).Accelerating the loading of large tables Explanation:A key advantage of data partitioning in a data warehouse is accelerating the loading of large tables.
Q67.
Why is planning for partitioning crucial in a data warehouse?

a.

It helps in creating unique B-Tree indexes

b.

It simplifies the process of regular purging

c.

It enables table merging for performance improvement

d.

Doing this after the data warehouse is deployed is time-consuming and difficult

Discuss
Answer: (d).Doing this after the data warehouse is deployed is time-consuming and difficult Explanation:Planning for partitioning is crucial in a data warehouse because doing this after the data warehouse is deployed is time-consuming and difficult.
Q68.
What is the primary benefit of partitioning a table in a data warehouse?

a.

Eliminates the need for indexing

b.

Accelerates the loading of large tables

c.

Simplifies the process of regular purging

d.

Reduces the need for backup and recovery

Discuss
Answer: (b).Accelerates the loading of large tables Explanation:The primary benefit of partitioning a table in a data warehouse is that it accelerates the loading of large tables.
Q69.
In vertical partitioning of a table, how are partitions separated?

a.

By grouping selected rows together

b.

By grouping selected columns together

c.

By dividing the table based on calendar dates

d.

By separating the recent events and past history

Discuss
Answer: (b).By grouping selected columns together Explanation:In vertical partitioning of a table, partitions are separated by grouping selected columns together.
Q70.
What is a benefit of horizontal partitioning in a data warehouse?

a.

Faster index building

b.

Improved data clustering

c.

Reduced downtime during data corruption

d.

Sequential access of related data

Discuss
Answer: (d).Sequential access of related data Explanation:A benefit of horizontal partitioning in a data warehouse is sequential access of related data.
Page 7 of 9

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