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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 9 of 13

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Q81.
How does vertical parallelism differ from horizontal parallelism in database processing?

a.

It focuses on data partitioning across multiple disks.

b.

It executes all query operations in parallel.

c.

It decomposes a query into subtasks and executes them in serial fashion.

d.

It avoids the wait times associated with data access.

Discuss
Answer: (c).It decomposes a query into subtasks and executes them in serial fashion. Explanation:Vertical parallelism decomposes a query into subtasks, and each subtask contains all the operations (e.g., index read, data read, join, and sort). These subtasks are executed in serial fashion, with data processed by one step and then passed to the next step, avoiding data wait times.
Q82.
What is the key advantage of the hybrid method in database processing?

a.

It focuses on data partitioning across multiple disks.

b.

It executes all query operations in parallel.

c.

It provides the best utilization of resources, optimal performance, and high scalability.

d.

It avoids the wait times associated with data access.

Discuss
Answer: (c).It provides the best utilization of resources, optimal performance, and high scalability. Explanation:The hybrid method combines both horizontal and vertical parallelism, resulting in optimal resource utilization, high performance, and scalability. It allows for parallel execution of different tasks and subtask decomposition within the same query.
Q83.
When selecting a DBMS for a data warehouse, which of the following is NOT a crucial feature to consider?

a.

Query optimizer

b.

Scalability in terms of the number of users and data volumes

c.

Load utility for data loading, recovery, and restart

d.

Hardware selection for parallel processing

Discuss
Answer: (d).Hardware selection for parallel processing Explanation:While selecting the DBMS for a data warehouse, features like query optimization, scalability, load utility, and administration are crucial. Hardware selection is a separate consideration from the choice of DBMS.
Q84.
What role does a query governor play in a DBMS for a data warehouse?

a.

It optimizes user queries for better performance.

b.

It manages the execution of different types of queries.

c.

It anticipates and aborts runaway queries.

d.

It provides high-performance data loading and recovery.

Discuss
Answer: (c).It anticipates and aborts runaway queries. Explanation:A query governor in a DBMS is responsible for anticipating and aborting runaway queries to prevent excessive resource consumption or performance issues.
Q85.
In the context of data warehousing, what is meant by "extensibility" in a DBMS?

a.

The ability to support hybrid extensions to OLAP databases

b.

The capacity to process both SQL and NoSQL data

c.

The capability to seamlessly connect with external data sources

d.

The feature that allows for unlimited storage capacity

Discuss
Answer: (a).The ability to support hybrid extensions to OLAP databases Explanation:Extensibility in a DBMS for data warehousing refers to the ability to support hybrid extensions to OLAP (Online Analytical Processing) databases, enabling more advanced analytics and data processing capabilities.
Q86.
What distinguishes the use of software tools in a data warehouse environment from an OLTP application?

a.

Greater reliance on programming languages

b.

Fewer third-party software tools

c.

More advanced GUI design software

d.

Extensive use of third-party software tools

Discuss
Answer: (d).Extensive use of third-party software tools Explanation:In a data warehouse environment, extensive use of third-party software tools is common, which sets it apart from OLTP applications.
Q87.
What is the significance of software tools in a data warehouse environment?

a.

Limited importance

b.

Not required at all

c.

Very significant

d.

Only useful for data extraction

Discuss
Answer: (c).Very significant Explanation:Software tools are very significant in a data warehouse environment as they support various functions and services.
Q88.
Which of the following functions do software tools NOT cover in a data warehouse?

a.

Data extraction and transformation

b.

Data quality

c.

Query and reporting

d.

Code generation for data modeling

Discuss
Answer: (d).Code generation for data modeling Explanation:Software tools in a data warehouse cover functions like data extraction, transformation, data quality, query, and reporting, but they may not be used for code generation in data modeling.
Q89.
Why is it important to design the architecture before choosing tools for a data warehouse?

a.

Tools are expensive

b.

Tools are not readily available

c.

Tools can drive the architecture

d.

Tools are unnecessary

Discuss
Answer: (c).Tools can drive the architecture Explanation:Designing the architecture before tool selection ensures that the chosen tools match the functions and services required for the architectural components.
Q90.
What is the problem with buying tools before establishing the architecture for an information delivery component in a data warehouse?

a.

Tools are expensive

b.

Tools don't work as promised

c.

Tools may not meet architectural requirements

d.

Tools are difficult to install

Discuss
Answer: (c).Tools may not meet architectural requirements Explanation:Buying tools before establishing the architecture can lead to tools that do not meet the architectural requirements of the data warehouse.
Page 9 of 13

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