Microsoft Certified Azure Data Fundamentals (Exam DP-900) Certification Guide: The comprehensive guide to passing the DP-900 exam on your first attempt
- Length: 300 pages
- Edition: 1
- Language: English
- Publisher: Packt Publishing
- Publication Date: 2022-11-25
- ISBN-10: 1803240636
- ISBN-13: 9781803240633
- Sales Rank: #804117 (See Top 100 Books)
Learn how to implement successful Azure Data projects and get the skills to clear the DP-900 certification exam with the help of mock tests and self-assessment scenarios for better preparation
Key Features
- Get the knowledge you need to pass the DP-900 exam on your first attempt
- Gain fundamental knowledge of the core concepts of working with data in Azure cloud data services
- Learn through a practical approach and test yourself with mock exams at the end of the book
Book Description
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.
What you will learn
- Explore the concepts of IaaS and PaaS database services on Azure
- Query, insert, update, and delete relational data using SQL
- Explore the concepts of data warehouses in Azure
- Perform data analytics with an Azure Synapse Analytics workspace
- Upload and retrieve data in Azure Cosmos DB and Azure HDInsight
- Provision and deploy non-relational data services in Azure
- Contextualize the knowledge with real-life use cases
- Test your progress with a mock exam
Who this book is for
This book is for data engineers, database administrators, or aspiring data professionals getting ready to take the DP-900 exam. It will also be helpful for those looking for a bit of guidance on how to be better equipped for Azure-related job roles such as Azure database administrator or Azure data engineer. A basic understanding of core data concepts and relational and non-relational data will help you make the most out of this book, but they’re not a pre-requisite.
Cover Title Page Copyright Dedication Contributors Table of Contents Preface Part 1: Core Data Concepts Chapter 1: Understanding the Core Data Terminologies Understanding the core data concepts What is data? How is data stored in a modern cloud environment? Describing a data solution Transactional databases Analytical databases Defining the data type and proper storage Characteristics of relational and non-relational databases A transactional workload An analytical workload Understanding data ingestion Understanding batch load Understanding data streaming Case study Summary Sample questions and answers Answer key Chapter 2: Exploring the Roles and Responsibilities in Data Domain Different workforces in a data domain Most common roles in a data domain Database Administrator Data engineer Data analyst Tasks and tools for database administration profiles Tasks of the DBA Tools for the DBA Tasks and tools for data engineer profiles Tasks of the data engineer Tools for the data engineer Tasks and tools for the data analyst Tasks of the data analyst Tools for the data analyst Case study Summary Sample questions and answers Answer key Chapter 3: Working with Relational Data Exploring the characteristics of relational data Tables and entities Relationship between entities Exploring relational data structures Data normalization Introducing SQL Key advantages of SQL Key disadvantages of SQL Understanding the categories of SQL commands DDL DML and DQL Describing the database components Views Stored procedures Triggers Indexes Case study Summary Sample questions and answers Answer key Chapter 4: Working with Non-Relational Data Exploring the characteristics of non-relational data Understanding the types of non-relational data Non-structured data Semi-structured data Non-relational data basic storage Exploring NoSQL databases What is a NoSQL database? Key-value store Document database Column family database Graph database Identifying non-relational database use cases Case study A 360-degree customer view Fraud detection – financial institutions Summary Sample questions and answers Answer key Chapter 5: Exploring Data Analytics Concepts Exploring data ingestion and processing Data pipelines Data ingestion types Data source connectors Exploring the analytical data store Data warehouse Data lake Hybrid approaches Exploring an analytical data model Facts and dimensions Exploring data visualization Case study Data-driven culture Summary Sample questions and answers Answer key Part 2: Relational Data in Azure Chapter 6: Integrating Relational Data on Azure Exploring relational Azure data services Elastic pool Use cases Summary Sample questions and answers Answer key Chapter 7: Provisioning and Configuring Relational Database Services in Azure Technical requirements Provisioning relational Azure data services Provisioning Azure SQL Database Provisioning Azure Database for PostgreSQL and MySQL Configuring relational databases on Azure Configuring Azure SQL Database Configuring and managing Azure Database for PostgreSQL and MySQL Summary Sample questions and answers Answer key Chapter 8: Querying Relational Data in Azure Technical requirements Introducing SQL on Azure Querying relational data in Azure SQL Database Common connection issues Querying relational data in Azure Database for PostgreSQL Connecting to Azure Database for PostgreSQL Querying Azure Database for PostgreSQL Summary Sample questions and answers Answer key Part 3: Non-Relational Data in Azure Chapter 9: Exploring Non-Relational Data Offerings in Azure Exploring Azure non-relational data stores Exploring Azure Blob storage Azure Data Lake Storage Gen2 Exploring Azure Files Exploring Azure Table storage Exploring Azure NoSQL databases Exploring Azure Cosmos DB Azure Cosmos DB APIs Core (SQL) API MongoDB API Table API Cassandra API Gremlin API Summary Sample questions and answers Answer key Chapter 10: Provisioning and Configuring Non-Relational Data Services in Azure Technical requirements Provisioning non-relational data services Provisioning Azure Cosmos DB Configuring Azure Cosmos DB Creating a sample Azure Cosmos DB database Provisioning an Azure storage account and Data Lake Storage Summary Sample questions and answers Answer key Part 4: Analytics Workload on Azure Chapter 11: Components of a Modern Data Warehouse Describing modern data warehousing Challenges of traditional data warehouses The birth of big data Azure HDInsight Modern data warehouse Azure for the modern data warehouse Exploring Azure data services for modern data warehouses Data ingestion and preparation (ELT/ETL) Data storage – Azure Data Lake Storage Gen2 Data ingestion – Azure Data Factory and Azure Synapse Analytics Data preparation – Azure Databricks Modern data warehouse – Azure Synapse Analytics Real-time data analytics – Azure Stream Analytics, Azure Synapse Data Explorer, and Spark streaming Azure Stream Analytics Azure Data Explorer and Azure Synapse Data Explorer pools Apache Spark Streaming Delta Lake Summary Sample questions and answers Answer key Chapter 12: Provisioning and Configuring Large-Scale Data Analytics in Azure Technical requirements Understanding common practices for data loading Provisioning an Azure Synapse workspace Practicing data load Data storage and processing Azure serverless SQL pool Azure dedicated SQL pool Azure Spark pools Azure Synapse Link Azure Synapse Data Explorer Azure Machine Learning Summary Sample questions and answers Answer key Chapter 13: Working with Power BI Technical requirements Introducing Power BI The building blocks of Power BI Exploring Power BI Desktop Creating a Power BI file Creating a connection Publishing a report Exploring Power BI Service Creating a dashboard Power BI mobile app Summary Sample questions and answers Answer key Chapter 14: DP-900 Mock Exam Practice test – questions Core data concepts Relational data on Azure Non-relational data on Azure Modern data warehouse analytics on Azure Practice test – answers and explanations Core data concepts Relational data on Azure Non-relational data on Azure Modern data warehouse analytics on Azure Summary Index About Packt Other Books You May Enjoy
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