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Dive deep into the fascinating world of Requirements as the Driving Force for Data warehousing with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Requirements as the Driving Force 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 Requirements as the Driving Force 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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Requirements as the Driving Force for Data warehousing MCQs | Page 2 of 8

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Q11.
What do users measure their success in terms of for automaker sales?

a.

Business dimensions

b.

Key measurements

c.

Source system data models

d.

Dimensional data model for data marts

Discuss
Answer: (b).Key measurements Explanation:Users measure their success in terms of key measurements such as actual sale price, MSRP, options price, full price, etc.
Q12.
What is the structure of the data model directly related to?

a.

Business dimensions

b.

Information package diagrams

c.

Source system data models

d.

Dimensional data model for data marts

Discuss
Answer: (a).Business dimensions Explanation:The structure of the data model is directly related to the number of business dimensions.
Q13.
Which components form the backbone of the dimensional data model?

a.

Source system data models

b.

Key measurements

c.

Business dimensions

d.

Both b and c

Discuss
Answer: (d).Both b and c Explanation:Business dimensions and key measurements form the backbone of the dimensional data model.
Q14.
What ensures that users can review the results in proper key measurements?

a.

Source system data models

b.

Business dimensions

c.

Information package diagrams

d.

Key measurements

Discuss
Answer: (c).Information package diagrams Explanation:Information package diagrams ensure that users can review the results in proper key measurements.
Q15.
What are used for business analysis and monitoring, and include metrics like sale units, revenue, cost, and profit margin?

a.

Business dimensions

b.

Information package diagrams

c.

Source system data models

d.

Dimensional data model for data marts

Discuss
Answer: (a).Business dimensions Explanation:Business dimensions are used for business analysis and monitoring, and they include metrics like sale units, revenue, cost, and profit margin.
Q16.
What is the importance of providing drill-down and roll-up facilities in the data model for analysis?

a.

It reduces the need for source data.

b.

It speeds up data retrieval.

c.

It enables users to view data at various levels of detail and aggregation.

d.

It simplifies the architecture of the data warehouse.

Discuss
Answer: (c).It enables users to view data at various levels of detail and aggregation. Explanation:Drill-down and roll-up facilities in the data model allow users to view data at various levels of detail and aggregation during analysis.
Q17.
What is the essential aspect of requirements definition related to the data model?

a.

Structuring the architecture

b.

Defining source data

c.

Specifying data storage techniques

d.

Identifying the types of summary and detail levels of data

Discuss
Answer: (d).Identifying the types of summary and detail levels of data Explanation:The essential aspect of requirements definition related to the data model is identifying the types of summary and detail levels of data.
Q18.
What is the primary purpose of data warehouse architecture planning?

a.

Inventing new components for the warehouse

b.

Sizing up each component for the environment

c.

Developing a proprietary database system

d.

Creating a unique data model

Discuss
Answer: (b).Sizing up each component for the environment Explanation:The primary purpose of data warehouse architecture planning is to size up each component for the environment.
Q19.
What are the major architectural components of a data warehouse?

a.

Data sources, data storage, and data transformation

b.

Source data, production data, and metadata

c.

Data extraction, data loading, and information delivery

d.

Source data, data staging, and management and control

Discuss
Answer: (b).Source data, production data, and metadata Explanation:The major architectural components of a data warehouse include source data, production data, and metadata.
Q20.
How does planning the overall architecture for a data warehouse involve reviewing the components?

a.

By designing new components

b.

By minimizing the size of each component

c.

By identifying the interfaces among the components

d.

By sizing up each component and setting parameters

Discuss
Answer: (d).By sizing up each component and setting parameters Explanation:Planning the overall architecture for a data warehouse involves reviewing each component, sizing up each component, and setting parameters.
Page 2 of 8

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