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Welcome to the Growth and Maintenance MCQs Page

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

Growth and Maintenance MCQs | Page 1 of 5

Explore more Topics under Data Warehousing and OLAP

Q1.
What major activities should the project team focus on immediately following the initial deployment of the data warehouse?

a.

Database tuning

b.

Infrastructure factors

c.

Administrative functions

d.

All of the above

Discuss
Answer: (d).All of the above Explanation:After the initial deployment, the project team must focus on database tuning, infrastructure factors, and administrative functions. These activities ensure the team is well poised for growth and the data warehouse is in good working order.
Q2.
What are the major review tasks that the project team must conduct immediately following the initial deployment?

a.

Review the testing process and suggest recommendations.

b.

Survey the methods used in the initial training sessions.

c.

Verify the results of the initial deployment, matching these with user expectations.

d.

All of the above

Discuss
Answer: (d).All of the above Explanation:The project team must review the testing process, survey training methods, and verify deployment results. These tasks are essential for documenting highlights and improving future releases.
Q3.
How is monitoring in a data warehouse environment different from monitoring an OLTP system?

a.

It focuses on infrastructure factors.

b.

It extends over many features and functions.

c.

It relies on event-driven methods only.

d.

It has minimal impact on system overhead.

Discuss
Answer: (b).It extends over many features and functions. Explanation:Monitoring in a data warehouse environment extends over many features and functions, providing a comprehensive view of system performance. This is a key difference from monitoring an OLTP system.
Q4.
What serves as the life-blood of the monitoring activity in a data warehouse?

a.

Data modeling

b.

Statistics

c.

Infrastructure planning

d.

End-user tools

Discuss
Answer: (b).Statistics Explanation:Statistics serve as the life-blood of the monitoring activity in a data warehouse. They provide essential information about system performance and growth trends.
Q5.
What are the two common methods used for collecting statistics on the working of the data warehouse?

a.

Sampling methods and event-driven methods

b.

Incremental methods and periodic methods

c.

Real-time methods and historical methods

d.

Predictive methods and reactive methods

Discuss
Answer: (a).Sampling methods and event-driven methods Explanation:The two common methods for collecting statistics on the working of the data warehouse are sampling methods and event-driven methods. Sampling measures specific aspects at regular intervals, while event-driven methods respond to specific events in the system.
Q6.
How do event-driven methods differ from sampling methods in data warehouse monitoring?

a.

Event-driven methods record statistics at regular intervals.

b.

Event-driven methods have minimal impact on system overhead.

c.

Event-driven methods record statistics only when specified events occur.

d.

Event-driven methods are less thorough than sampling methods.

Discuss
Answer: (c).Event-driven methods record statistics only when specified events occur. Explanation:Event-driven methods record statistics only when specified events occur, providing a more thorough but potentially higher system overhead approach.
Q7.
What components are involved in tools that collect monitoring statistics in a data warehouse environment?

a.

Collector and Analyzer

b.

Sampler and Interpreter

c.

Recorder and Processor

d.

Observer and Evaluator

Discuss
Answer: (a).Collector and Analyzer Explanation:Tools that collect monitoring statistics typically consist of a data collector component that gathers statistics and an analyzer component that interprets the results.
Q8.
What is the primary difference between physical disk storage space utilization and memory buffer activity in monitoring statistics?

a.

Disk space is used for long-term storage, while memory buffers are temporary.

b.

Disk space is managed by the host operating system, while memory buffers are managed by the database server.

c.

Disk space utilization relates to storage, while memory buffer activity involves data retrieval.

d.

Disk space utilization is event-driven, while memory buffer activity is sampled at intervals.

Discuss
Answer: (c).Disk space utilization relates to storage, while memory buffer activity involves data retrieval. Explanation:Disk space utilization pertains to storage, while memory buffer activity involves the usage of buffers for data retrieval and processing.
Q9.
What is an example of a profile statistic in a data warehouse?

a.

Memory buffer activity

b.

Input – output performance

c.

Number of distinct entity occurrences

d.

Buffer cache usage

Discuss
Answer: (c).Number of distinct entity occurrences Explanation:A profile statistic in a data warehouse could be the number of distinct entity occurrences, such as the count of customers or products.
Q10.
Which action is prompted by monitoring statistics for growth planning in a data warehouse?

a.

Decrease memory buffer allocation.

b.

Reduce disk space for existing database tables.

c.

Reorganize staging area files for less data volume.

d.

Plan for new disk space for additional tables.

Discuss
Answer: (d).Plan for new disk space for additional tables. Explanation:Monitoring statistics for growth planning may prompt the action of planning for new disk space to accommodate additional tables in the data warehouse.
Page 1 of 5

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