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Welcome to the Infrastructure as the Foundation for Data Warehousing MCQs Page

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

Infrastructure as the Foundation for Data Warehousing MCQs | Page 8 of 13

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Q71.
What two features are critical in a data warehouse, and the DBMS vendors have provided parallel processing to improve them?

a.

Data transformation and indexing

b.

Load balancing and query performance

c.

Mass loading and retrieval of data

d.

Replication and aggregation

Discuss
Answer: (b).Load balancing and query performance Explanation:Load balancing and query performance are critical in a data warehouse, and parallel processing is provided to improve them.
Q72.
Which of the following operations can be parallelized by most current database software in a multi-processor environment?

a.

Creating and rebuilding indexes

b.

OLAP cube creation

c.

Backup and restore

d.

Transaction log management

Discuss
Answer: (a).Creating and rebuilding indexes Explanation:Most current database software can parallelize operations such as creating and rebuilding indexes in a multi-processor environment.
Q73.
What is the responsibility of the query dispatcher software in a database system that uses parallel processing?

a.

Executing the queries

b.

Distributing the units of work among query server processes

c.

Balancing the load across different database servers

d.

Assembling the query results

Discuss
Answer: (b).Distributing the units of work among query server processes Explanation:The query dispatcher software is responsible for distributing the units of work among the pool of available query server processes in a parallel processing database system.
Q74.
In the context of database processing, what does "interquery parallelization" refer to?

a.

Parallel execution of multiple queries simultaneously

b.

Parallel execution of different operations within the same query

c.

Sequential execution of multiple queries to increase throughput

d.

Sequential execution of different operations within the same query

Discuss
Answer: (a).Parallel execution of multiple queries simultaneously Explanation:Interquery parallelization allows multiple queries to be executed concurrently, but each query is processed serially.
Q75.
What is a limitation of interquery parallelization in database systems?

a.

It doesn't support concurrent users.

b.

It requires a specialized type of database hardware.

c.

Parts of the same query do not execute in parallel.

d.

It cannot be used in SMP systems.

Discuss
Answer: (c).Parts of the same query do not execute in parallel. Explanation:In interquery parallelization, multiple queries are processed concurrently, but parts of the same query do not execute in parallel.
Q76.
What is the main advantage of intraquery parallelization in a database system?

a.

It allows parallel execution of multiple queries.

b.

It improves throughput and supports more concurrent users.

c.

It simplifies query optimization.

d.

It eliminates the need for indexing.

Discuss
Answer: (b).It improves throughput and supports more concurrent users. Explanation:Intraquery parallelization allows the parallel execution of different operations within the same query, improving throughput and supporting more concurrent users.
Q77.
How does intraquery parallelization work in a database system?

a.

It splits the query into smaller queries.

b.

It executes all operations of the query serially.

c.

It processes different parts of the query in parallel on a single processor.

d.

It consolidates intermediary results from parallel operations.

Discuss
Answer: (c).It processes different parts of the query in parallel on a single processor. Explanation:Intraquery parallelization splits the query into its lower-level operations and executes each part in parallel on a single processor.
Q78.
In the context of intraquery parallelization, what is meant by "the consolidation of intermediary results"?

a.

Combining results from multiple queries

b.

Combining results from different parts of the same query

c.

Storing query results for future use

d.

Summarizing the results for reporting

Discuss
Answer: (b).Combining results from different parts of the same query Explanation:In intraquery parallelization, intermediary results from different parts of the same query are consolidated to produce the final result set.
Q79.
What is horizontal parallelism in the context of database processing?

a.

Data partitioning across multiple disks

b.

Parallel execution of different tasks in a query

c.

Pipelined execution of subtasks in a query

d.

The decomposition of tasks into subtasks

Discuss
Answer: (b).Parallel execution of different tasks in a query Explanation:Horizontal parallelism involves the parallel execution of different tasks within a query. Each task is processed concurrently, but the tasks within the same query are executed serially by a single server process.
Q80.
What is a limitation of horizontal parallelism in database processing?

a.

It results in data wait times until all needed data is read.

b.

It requires advanced decomposition of tasks.

c.

It executes all component query operations in parallel.

d.

It avoids data wait times.

Discuss
Answer: (a).It results in data wait times until all needed data is read. Explanation:Horizontal parallelism can result in data wait times because all necessary data must be read before the next task in the query can begin, leading to potential delays.
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