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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 5 of 5

Explore more Topics under Data Warehousing and OLAP

Q41.
What is a useful suggestion for ETL (data extraction, transformation, loading) management in a data warehouse?

a.

Delay daily extraction jobs to avoid system load.

b.

Ignore exceptions thrown out by the transformation functions.

c.

Run extraction jobs on an irregular schedule.

d.

Install an alert system for exceptional conditions.

Discuss
Answer: (d).Install an alert system for exceptional conditions. Explanation:Installing an alert system for exceptional conditions is a useful suggestion for ETL management in a data warehouse.
Q42.
What is a key consideration for ensuring proper handling of slowly changing dimensions in ETL management?

a.

Run extraction jobs on an irregular schedule.

b.

Check the proper handling of slowly changing dimensions.

c.

Ignore reconciliation between source system record counts and extracted file counts.

d.

Delay daily extraction jobs to avoid system load.

Discuss
Answer: (b).Check the proper handling of slowly changing dimensions. Explanation:Checking the proper handling of slowly changing dimensions is a key consideration in ETL management.
Q43.
What is an implication of data model revisions in a data warehouse?

a.

Increased data replication techniques.

b.

Additional predefined queries and preformatted reports.

c.

Decreased storage allocations.

d.

Reduced load image creation processes.

Discuss
Answer: (b).Additional predefined queries and preformatted reports. Explanation:An implication of data model revisions in a data warehouse includes additional predefined queries and preformatted reports.
Q44.
Why is caution advised when enhancing end-user tools in a data warehouse?

a.

Users are resistant to change.

b.

Enhancing tools does not impact users directly.

c.

Users do not benefit from new tools.

d.

Changes to end-user tools relate directly to users.

Discuss
Answer: (d).Changes to end-user tools relate directly to users. Explanation:Caution is advised when enhancing end-user tools in a data warehouse because changes to end-user tools relate directly to users.
Q45.
What is a tip for adopting a different tool set for end-users in a data warehouse?

a.

Ensure compatibility with some data warehouse components.

b.

Switch all users over to the new tool set simultaneously.

c.

Avoid integration of end-user metadata.

d.

Plan the change carefully and proceed with caution.

Discuss
Answer: (d).Plan the change carefully and proceed with caution. Explanation:A tip for adopting a different tool set for end-users in a data warehouse is to plan the change carefully and proceed with caution.
Q46.
What is a practical suggestion for ongoing fine-tuning of a data warehouse?

a.

Keep all indexes regardless of usage.

b.

Drop indexes that are no longer used.

c.

Review query performance only monthly.

d.

Avoid investigating long-running queries.

Discuss
Answer: (b).Drop indexes that are no longer used. Explanation:A practical suggestion for ongoing fine-tuning of a data warehouse is to drop indexes that are no longer used.
Q47.
How can you address sudden issues with queries causing problems in a data warehouse?

a.

Ignore user complaints and wait for issues to resolve on their own.

b.

Have a regular schedule for ongoing fine-tuning.

c.

Drop all indexes and recreate them.

d.

Be prepared for ad hoc fine-tuning needs and allocate staff for such situations.

Discuss
Answer: (d).Be prepared for ad hoc fine-tuning needs and allocate staff for such situations. Explanation:To address sudden issues with queries causing problems in a data warehouse, be prepared for ad hoc fine-tuning needs and allocate staff for such situations.
Q48.
What is a key aspect of ongoing monitoring of a data warehouse?

a.

Ignoring statistics collection after the initial deployment.

b.

Reviewing load distribution at different times every month.

c.

Collecting statistics on a variety of indicators for growth planning and fine-tuning.

d.

Conducting review sessions with the project team.

Discuss
Answer: (c).Collecting statistics on a variety of indicators for growth planning and fine-tuning. Explanation:A key aspect of ongoing monitoring of a data warehouse is collecting statistics on a variety of indicators for growth planning and fine-tuning.
Q49.
What is a function of the user support tier in a data warehouse?

a.

Managing data growth.

b.

Determining the content of needed training.

c.

Reviewing load distribution.

d.

Delivering appropriate support for data content, applications, and tools.

Discuss
Answer: (d).Delivering appropriate support for data content, applications, and tools. Explanation:The function of the user support tier in a data warehouse is delivering appropriate support for data content, applications, and tools.
Q50.
What is a part of ongoing management and administration in a data warehouse?

a.

Conducting ad hoc fine-tuning needs.

b.

Ignoring platform upgrades.

c.

Avoiding data model revisions.

d.

Managing data growth.

Discuss
Answer: (d).Managing data growth. Explanation:Managing data growth is a part of ongoing management and administration in a data warehouse.
Page 5 of 5

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