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Welcome to the OLAP in the Data Warehouse MCQs Page

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

OLAP in the Data Warehouse MCQs | Page 8 of 13

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Q71.
In the ROLAP model, how is data stored?

a.

As precalculated and prefabricated multidimensional data cubes

b.

In proprietary multidimensional databases (MDDBs)

c.

As rows and columns in a relational data model

d.

As virtual multidimensional data cubes

Discuss
Answer: (c).As rows and columns in a relational data model Explanation:In the ROLAP model, data is stored as rows and columns in a relational data model.
Q72.
What is created in the ROLAP model to hide the storage structure and present data multidimensionally?

a.

Precalculated cubes

b.

Virtual cubes

c.

Metadata layer

d.

Proprietary multidimensional databases (MDDBs)

Discuss
Answer: (c).Metadata layer Explanation:In the ROLAP model, a metadata layer is created to hide the storage structure and present data multidimensionally.
Q73.
What does the metadata layer in the ROLAP model support?

a.

Mapping of dimensions to relational tables

b.

Storage of multidimensional hypercubes

c.

Creation of virtual multidimensional data cubes

d.

Summarizations in multidimensional databases

Discuss
Answer: (a).Mapping of dimensions to relational tables Explanation:The metadata layer in the ROLAP model supports the mapping of dimensions to relational tables.
Q74.
What is the role of the analytical server in the ROLAP model?

a.

Storing precalculated cubes

b.

Creating multidimensional views on the fly

c.

Aggregating data in MDDBs

d.

Serving as a special server for OLAP engines

Discuss
Answer: (b).Creating multidimensional views on the fly Explanation:In the ROLAP model, the analytical server in the application layer creates multidimensional views on the fly.
Q75.
What is a true characteristic of ROLAP?

a.

Stores data in a multidimensional form

b.

Supports precalculated cubes

c.

Stores data in a relational form

d.

Requires static multidimensional structures

Discuss
Answer: (c).Stores data in a relational form Explanation:A true characteristic of ROLAP is that it stores data in a relational form.
Q76.
What does local hypercubing provide as a variation of ROLAP?

a.

A local, multidimensional view of the data

b.

Precalculated cubes

c.

A static multidimensional structure

d.

Query performance

Discuss
Answer: (a).A local, multidimensional view of the data Explanation:Local hypercubing provides a small, local, multidimensional database for a user's analysis.
Q77.
In the ROLAP versus MOLAP comparison, what does MOLAP excel in?

a.

Query performance

b.

Query complexity

c.

Aggregation support

d.

Relational data storage

Discuss
Answer: (a).Query performance Explanation:MOLAP excels in query performance in the ROLAP versus MOLAP comparison.
Q78.
What consideration does the choice between ROLAP and MOLAP depend on?

a.

Query performance only

b.

Query complexity only

c.

Both query performance and query complexity

d.

Relational data storage only

Discuss
Answer: (c).Both query performance and query complexity Explanation:The choice between ROLAP and MOLAP depends on both query performance and query complexity.
Q79.
OLAP implementation considerations include two key issues related to the MOLAP model. What is the first issue?

a.

Lack of standardization

b.

Scalability

c.

Client interface

d.

Volumes of detailed data

Discuss
Answer: (a).Lack of standardization Explanation:The first issue in OLAP implementation considerations is the lack of standardization, as each vendor tool has its own client interface.
Q80.
What can highly normalized data in the data warehouse give rise to when performing complex analysis?

a.

Lack of standardization

b.

Scalability issues

c.

Processing overhead

d.

Multidimensional design

Discuss
Answer: (c).Processing overhead Explanation:Highly normalized data in the data warehouse can give rise to processing overhead when performing complex analysis.
Page 8 of 13

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