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Microsoft Certified Azure Data Fundamentals (Exam DP-900) Certification Guide

You're reading from   Microsoft Certified Azure Data Fundamentals (Exam DP-900) Certification Guide The comprehensive guide to passing the DP-900 exam on your first attempt

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Product type Paperback
Published in Nov 2022
Publisher Packt
ISBN-13 9781803240633
Length 300 pages
Edition 1st Edition
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Author (1):
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Marcelo Leite Marcelo Leite
Author Profile Icon Marcelo Leite
Marcelo Leite
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Toc

Table of Contents (21) Chapters Close

Preface 1. Part 1: Core Data Concepts
2. Chapter 1: Understanding the Core Data Terminologies FREE CHAPTER 3. Chapter 2: Exploring the Roles and Responsibilities in Data Domain 4. Chapter 3: Working with Relational Data 5. Chapter 4: Working with Non-Relational Data 6. Chapter 5: Exploring Data Analytics Concepts 7. Part 2: Relational Data in Azure
8. Chapter 6: Integrating Relational Data on Azure 9. Chapter 7: Provisioning and Configuring Relational Database Services in Azure 10. Chapter 8: Querying Relational Data in Azure 11. Part 3: Non-Relational Data in Azure
12. Chapter 9: Exploring Non-Relational Data Offerings in Azure 13. Chapter 10: Provisioning and Configuring Non-Relational Data Services in Azure 14. Part 4: Analytics Workload on Azure
15. Chapter 11: Components of a Modern Data Warehouse 16. Chapter 12: Provisioning and Configuring Large-Scale Data Analytics in Azure 17. Chapter 13: Working with Power BI 18. Chapter 14: DP-900 Mock Exam 19. Index 20. Other Books You May Enjoy

Practice test – answers and explanations

Now that you have marked up your answers to the questions, in the following sections, we’ll discuss how we can eliminate incorrect choices and mark the correct answer for these questions.

Core data concepts

  1. Select the correct statement:
    1. ( ) Extract, transform, and load (ETL) can limit the amount of sensitive data that is transferred to target system.
    2. ( ) Extract, load, and transform (ELT) reduces the amount of time needed to copy substantial amounts of data to the target system.
    3. (X) Extract, load, and transform (ELT) transforms data utilizing a computational resource that is not dependent on the source or target system.
    4. ( ) Extract, transform, and load (ETL) transforms data utilizing a computational resource that is not dependent on the source or target systems

Explanation

  • Option A is incorrect because, in ETL processes, it is often not evaluated whether the data is sensitive or not. For this analysis...
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