Welcome to the Planning and Project Management MCQs Page

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

Planning and Project Management MCQs | Page 4 of 10

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

Defining the Business Requirements

05

Requirements as the Driving Force for Data warehousing 🔒

06

Architectural Components 🔒

07

Infrastructure as the Foundation for Data Warehousing 🔒

08

Role of Metadata in Data Warehousing 🔒

09

Principles of Dimensional Modeling

10

Advanced Topics in Dimensional Modeling 🔒

11

Data Extraction,Transformation and Loading 🔒

12

Importance of Data Quality

13

Matching Information to the Classes of Users

14

OLAP in the Data Warehouse 🔒

15

Data Warehousing and the Web 🔒

16

Data Mining Basics 🔒

17

The Physical Design Process 🔒

18

Data Warehouse Deployment 🔒

19

Growth and Maintenance

20

Important Terms and Definitions

Q31.

Who typically conducts the readiness assessment in a data warehouse project?

Data analysts

Project manager with outside expert assistance

Executive sponsor

End-users

Discuss

Answer: (b).Project manager with outside expert assistance Explanation:The readiness assessment is typically conducted by the project manager with the assistance of an outside expert.

Q32.

What is one of the purposes of the readiness assessment report in a data warehouse project?

To enforce orderliness in the project

To identify project deliverables

To assess corporate commitment

To create a project schedule

Discuss

Answer: (c).To assess corporate commitment Explanation:One of the purposes of the readiness assessment report is to assess corporate commitment.

Q33.

How does the life cycle approach differ in a data warehouse project compared to a traditional system development project?

The life cycle approach in a data warehouse project is more structured.

The life cycle approach in a data warehouse project is a waterfall method.

The life cycle approach in a data warehouse project includes iterative tasks.

The life cycle approach in a data warehouse project is less complex.

Discuss

Answer: (c).The life cycle approach in a data warehouse project includes iterative tasks. Explanation:The life cycle approach in a data warehouse project includes iterative tasks due to the complexity of the project.

Q34.

Which of the following is NOT one of the broad functional components of a data warehouse?

Data acquisition

Data storage

Information delivery

Data processing

Discuss

Answer: (d).Data processing Explanation:Data processing is not one of the broad functional components of a data warehouse.

Q35.

What does the project plan include in a data warehouse project?

List of source systems

Training schedule for end-users

Project schedule and assignments

User expectations

Discuss

Answer: (c).Project schedule and assignments Explanation:The project plan in a data warehouse project includes the project schedule, lists of tasks and assignments, and provides for monitoring progress.

Q36.

Which of the following are the general architecture components of a data warehouse?

Data processing, data modeling, data transformation

Data acquisition, data storage, information delivery

Data entry, data cleansing, data reporting

Data retrieval, data migration, data archiving

Discuss

Answer: (b).Data acquisition, data storage, information delivery Explanation:The general architecture components of a data warehouse are data acquisition, data storage, and information delivery.

Q37.

What is the purpose of the three tracks in the development phases of a data warehouse project?

To emphasize data modeling

To break down the project into different phases

To provide redundancy in case of failures

To focus on different functional components

Discuss

Answer: (d).To focus on different functional components Explanation:The purpose of the three tracks is to focus on different functional components within the data warehouse project.

Q38.

How does the architecture definition and infrastructure establishment fit into the development phases of a data warehouse project?

They are separate phases after the deployment phase.

They are part of the design and construction phases.

They are part of the growth and maintenance phase.

They are not relevant to a data warehouse project.

Discuss

Answer: (b).They are part of the design and construction phases. Explanation:Architecture definition and infrastructure establishment are part of the design and construction phases of a data warehouse project.

Q39.

What should project teams do if data quality is a problem in their company?

Ignore it and focus on data acquisition.

Pay special attention to data storage.

Address data quality as part of the construction phase.

Pay special attention to the related phase.

Discuss

Answer: (d).Pay special attention to the related phase. Explanation:If data quality is a problem in a company, the project team should pay special attention to the related phase, which is likely to be part of the construction phase.

Q40.

What core values are emphasized in the agile development methodology for data warehouse development?

Complexity and avoiding feedback

Constant feedback, simplicity, communication, and learning from mistakes

Rewarding complexity and ignoring mistakes

Frequent expansion of the work week

Discuss

Answer: (b).Constant feedback, simplicity, communication, and learning from mistakes Explanation:The core values emphasized in the agile development methodology for data warehouse development include constant feedback, simplicity, communication, and learning from mistakes.

Page 4 of 10

Building Blocks of Data Warehouse 🔒

Trends in Data Warehousing 🔒

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 Warehousing and the Web 🔒

Data Mining Basics 🔒

The Physical Design Process 🔒

Data Warehouse Deployment 🔒

Welcome to the Planning and Project Management MCQs Page

Planning and Project Management MCQs | Page 4 of 10

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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