Book Image

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

By : Marcelo Leite
5 (1)
Book Image

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

5 (1)
By: Marcelo Leite

Overview of this book

Passing the DP-900 Microsoft Azure Data Fundamentals exam opens the door to a myriad of opportunities for working with data services in the cloud. But it is not an easy exam and you'll need a guide to set you up for success and prepare you for a career in Microsoft Azure. Absolutely everything you need to pass the DP-900 exam is covered in this concise handbook. After an introductory chapter covering the core terms and concepts, you'll go through the various roles related to working with data in the cloud and learn the similarities and differences between relational and non-relational databases. This foundational knowledge is crucial, as you'll learn how to provision and deploy Azure's relational and non-relational services in detail later in the book. You'll also gain an understanding of how to glean insights with data analytics at both small and large scales, and how to visualize your insights with Power BI. Once you reach the end of the book, you'll be able to test your knowledge with practice tests with detailed explanations of the correct answers. By the end of this book, you will be armed with the knowledge and confidence to not only pass the DP-900 exam but also have a solid foundation from which to embark on a career in Azure data services.
Table of Contents (21 chapters)
1
Part 1: Core Data Concepts
7
Part 2: Relational Data in Azure
11
Part 3: Non-Relational Data in Azure
14
Part 4: Analytics Workload on Azure

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...