Welcome to the Data Extraction,Transformation and Loading MCQs Page

Dive deep into the fascinating world of Data Extraction,Transformation and Loading with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Data Extraction,Transformation and Loading, 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 Extraction,Transformation and Loading, 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 Extraction,Transformation and Loading. 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 Extraction,Transformation and Loading. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Data Extraction,Transformation and Loading MCQs | Page 9 of 15

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

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

Q81.

What is the term used to describe the process of applying ongoing changes to the data warehouse in a periodic manner?

Initial load

Incremental load

Full refresh

Data staging

Discuss

Answer: (b).Incremental load Explanation:The process of applying ongoing changes to the data warehouse in a periodic manner is referred to as the "incremental load."

Q82.

When does a "full refresh" in data loading occur?

When changes need to be applied periodically

When only a few tables need to be refreshed

When all tables are completely erased and reloaded with fresh data

When a small portion of data needs to be loaded

Discuss

Answer: (c).When all tables are completely erased and reloaded with fresh data Explanation:A "full refresh" in data loading occurs when all tables are completely erased and reloaded with fresh data.

Q83.

Why is it important to divide the whole load process into smaller chunks when loading the data warehouse?

To increase the complexity of data loading

To minimize the impact on the network

To keep some parts of the data warehouse operational while loading others

To reduce the number of load programs required

Discuss

Answer: (c).To keep some parts of the data warehouse operational while loading others Explanation:Dividing the load process into smaller chunks allows you to keep some parts of the data warehouse operational while loading others.

Q84.

What is a key consideration when transporting load images to the data warehouse server from a different location?

The number of load programs required

The impact on the network

The size of the data warehouse

The bandwidth needed for the transmission

Discuss

Answer: (d).The bandwidth needed for the transmission Explanation:A key consideration when transporting load images is the necessary bandwidth needed for the transmission.

Q85.

In the context of data loading, what is the primary difference between an "append" and a "load" operation?

Append adds incoming data while preserving existing data, while load replaces existing data with incoming data.

Append and load are essentially the same operation with no difference.

Append wipes out existing data and applies incoming data, while load handles duplicates during the process.

Append applies incoming data to an empty table, while load applies incoming data to a table with existing data.

Discuss

Answer: (a).Append adds incoming data while preserving existing data, while load replaces existing data with incoming data. Explanation:The primary difference between an "append" and a "load" operation is that append adds incoming data while preserving existing data, whereas load replaces existing data with incoming data.

Q86.

What happens during a "destructive merge" when the primary key of an incoming record matches the key of an existing record?

The incoming record is allowed to be added as a duplicate.

The matching target record is updated with the incoming data.

The incoming record is rejected during the merge process.

The incoming record is added to the target table without updating existing records.

Discuss

Answer: (b).The matching target record is updated with the incoming data. Explanation:During a "destructive merge," when the primary key of an incoming record matches the key of an existing record, the matching target record is updated with the incoming data.

Q87.

How is "constructive merge" different from "destructive merge" in data loading?

Constructive merge updates existing records, while destructive merge leaves them unchanged.

Constructive merge allows incoming records to be added as duplicates, while destructive merge rejects duplicates.

Constructive merge marks added records as superseding the old ones, while destructive merge does not.

Constructive merge matches primary keys and updates existing records, while destructive merge does not.

Discuss

Answer: (c).Constructive merge marks added records as superseding the old ones, while destructive merge does not. Explanation:"Constructive merge" marks added records as superseding the old ones when the primary key of an incoming record matches the key of an existing record, which is different from "destructive merge."

Q88.

Which mode of applying data is used when the target table is already empty before loading?

Append

Destructive Merge

Constructive Merge

Load

Discuss

Answer: (d).Load Explanation:The "load" mode is used when the target table is already empty before loading, and it simply applies the data from the incoming file.

Q89.

In which scenario during the initial load of a data warehouse table is the "load" mode typically used?

When the load runs for a single table must be scheduled to run on several days

When a single run creates the database tables from scratch

When index creation on mass loads is time-consuming

When you need to apply ongoing changes from the source systems

Discuss

Answer: (b).When a single run creates the database tables from scratch Explanation:The "load" mode is typically used during the initial load when a single run creates the database tables from scratch.

Q90.

What mode is appropriate for preserving the periodic nature of changes in incremental loads of a data warehouse?

Append mode

Constructive merge mode

Destructive merge mode

Load mode

Discuss

Answer: (b).Constructive merge mode Explanation:The "constructive merge" mode is appropriate for preserving the periodic nature of changes in incremental loads of a data warehouse.

Page 9 of 15

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 🔒

OLAP in the Data Warehouse 🔒

Data Warehousing and the Web 🔒

Data Mining Basics 🔒

The Physical Design Process 🔒

Data Warehouse Deployment 🔒

Welcome to the Data Extraction,Transformation and Loading MCQs Page

Data Extraction,Transformation and Loading MCQs | Page 9 of 15

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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