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

Sample questions and answers

Let’s evaluate a few sample questions in preparation for the exam before starting the next chapter:

  1. What constitutes an Azure Table storage key?
    1. Partition key and row key
    2. Table name and column name
    3. Row number
    4. Non-structured data
  2. What should you do with an existing Azure storage account to enable Azure Synapse Analytics to use it as a data lake?
    1. Add an Azure Files share
    2. Create Azure Storage tables for the data you want to analyze
    3. Upgrade the account to enable a hierarchical namespace and create a blob container
    4. Start data ingestion
  3. Why would you use Azure Files storage?
    1. To share files that are stored on-premises with users located at other sites
    2. To enable users at different sites to share files
    3. To store large binary data files containing images or other unstructured data
    4. To store video and audio files only
  4. Which Azure Cosmos DB API should you use to store and query JSON documents?
    1. Core (SQL) API
    2. Cassandra API
    3. Table API
    4. Gremlin API
  5. Which Azure...