Welcome to the Data Warehousing and the Web MCQs Page

Dive deep into the fascinating world of Data Warehousing and the Web with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Data Warehousing and the Web, a crucial aspect of Data Warehousing and OLAP. In this section, you will encounter a diverse range of MCQs that cover various aspects of Data Warehousing and the Web, 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.

Check out the MCQs below to embark on an enriching journey through Data Warehousing and the Web. 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 Data Warehousing and the Web. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Data Warehousing and the Web MCQs | Page 9 of 13

Explore more Topics under Data Warehousing and OLAP

01

The Compelling Need for Data Warehousing

02

Building Blocks of Data Warehouse 🔒

03

Trends in Data Warehousing 🔒

04

Planning and Project Management 🔒

05

Defining the Business Requirements

06

Requirements as the Driving Force for Data warehousing 🔒

07

Architectural Components 🔒

08

Infrastructure as the Foundation for Data Warehousing 🔒

09

Role of Metadata in Data Warehousing 🔒

10

Principles of Dimensional Modeling

11

Advanced Topics in Dimensional Modeling 🔒

12

Data Extraction,Transformation and Loading 🔒

13

Importance of Data Quality

14

Matching Information to the Classes of Users

15

OLAP in the Data Warehouse 🔒

16

Data Mining Basics 🔒

17

The Physical Design Process 🔒

18

Data Warehouse Deployment 🔒

19

Growth and Maintenance

20

Important Terms and Definitions

Q81.

What are two problems associated with an OLAP engine that generates SQL to access summary data and performs all processing on a middle tier?

Reduced network traffic and small memory requirements

Linear performance curve and optimal use of DBMS potential

Heavy network traffic and large memory requirements

Balanced system processing and optimized network traffic

Discuss

Answer: (c).Heavy network traffic and large memory requirements Explanation:Two problems associated with this approach are heavy network traffic and large memory requirements.

Q82.

What is a potential issue with an OLAP engine that relies completely on the RDBMS for multidimensional processing?

Reduced network traffic

Improved scalability

Linear performance curve with a gradual inclination

Steep performance curve due to underutilized DBMS potential

Discuss

Answer: (d).Steep performance curve due to underutilized DBMS potential Explanation:An issue with an OLAP engine depending on the RDBMS is that it may result in a steep performance curve due to underutilized DBMS potential.

Q83.

What is an advantage of an intelligent OLAP engine in distributing joins, aggregations, and calculations?

Increased network traffic

Heavy memory requirements

Balanced system processing and optimized network traffic

Linear performance curve with a gradual inclination

Discuss

Answer: (c).Balanced system processing and optimized network traffic Explanation:An advantage of an intelligent OLAP engine is that it can distribute joins, aggregations, and calculations to balance system processing and optimize network traffic.

Q84.

What does the intelligent OLAP engine have the ability to do regarding the type of request and its optimal processing location?

Generate SQL for all requests

Distribute joins and aggregations to the middle tier

Determine the type of request and where it will be performed optimally

Rely completely on the RDBMS for all processing

Discuss

Answer: (c).Determine the type of request and where it will be performed optimally Explanation:The intelligent OLAP engine has the ability to determine the type of request and where it will be performed optimally.

Q85.

How does the intelligent OLAP engine contribute to system processing in a Web-enabled data warehouse?

Heavy reliance on the RDBMS

Optimal use of DBMS potential

Balanced system processing and optimized network traffic

Steep performance curve due to underutilized DBMS potential

Discuss

Answer: (c).Balanced system processing and optimized network traffic Explanation:The intelligent OLAP engine contributes to balanced system processing and optimized network traffic in a Web-enabled data warehouse.

Q86.

What is the primary purpose of a data warehouse in the context of the Web?

Optimization of network traffic

Provision of information

Reduced memory requirements

Improved DBMS potential

Discuss

Answer: (b).Provision of information Explanation:The primary purpose of a data warehouse in the context of the Web is to provide information.

Q87.

How has the Web changed the design and deployment of data warehouses?

Reduced the value of data warehouses

Increased reliance on traditional methods

Opened up remarkable possibilities

Limited the scope of data warehouses

Discuss

Answer: (c).Opened up remarkable possibilities Explanation:The Web has changed the design and deployment of data warehouses by opening up remarkable possibilities.

Q88.

What is the result of matching up the features of the data warehouse with the characteristics of the Web?

Reduced adaptability

Increased complexity

Expanded value to a wider array of users

Decreased usability

Discuss

Answer: (c).Expanded value to a wider array of users Explanation:The result of matching up the features of the data warehouse with the characteristics of the Web is expanded value to a wider array of users.

Q89.

How is Web-based information delivery different from traditional methods?

Less inclusive

More complex

More inclusive and easier to use

Limited to internal users

Discuss

Answer: (c).More inclusive and easier to use Explanation:Web-based information delivery is more inclusive and easier to use compared to traditional methods.

Q90.

What considerations are we now ready to review after covering Web-based information delivery and OLAP in relation to the Web?

Design and deployment of traditional data warehouses

Considerations for building a Web-enabled data warehouse

Implementation of browser plug-ins

Utilization of pre-created HTML documents

Discuss

Answer: (b).Considerations for building a Web-enabled data warehouse Explanation:After covering Web-based information delivery and OLAP in relation to the Web, we are now ready to review considerations for building a Web-enabled data warehouse.

Page 9 of 13

Building Blocks of Data Warehouse 🔒

Trends in Data Warehousing 🔒

Planning and Project Management 🔒

Requirements as the Driving Force for Data warehousing 🔒

Architectural Components 🔒

Infrastructure as the Foundation for Data Warehousing 🔒

Role of Metadata in Data Warehousing 🔒

Advanced Topics in Dimensional Modeling 🔒

Data Extraction,Transformation and Loading 🔒

OLAP in the Data Warehouse 🔒

Data Mining Basics 🔒

The Physical Design Process 🔒

Data Warehouse Deployment 🔒

Welcome to the Data Warehousing and the Web MCQs Page

Data Warehousing and the Web MCQs | Page 9 of 13

Explore more Topics under Data Warehousing and OLAP

The Compelling Need for Data Warehousing

Defining the Business Requirements

Principles of Dimensional Modeling

Importance of Data Quality

Matching Information to the Classes of Users

Growth and Maintenance

Important Terms and Definitions

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