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MICROSOFT CERTIFIED AZURE DATA FUNDAMENTALS (EXAM DP-900) CERTIFICATION GUIDE the comprehensive guide to passing the DP-900 exam on your first attempt /
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 know...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
[S.l.] :
PACKT PUBLISHING LIMITED,
2022.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Leite, Marcelo, |e author. | |
| 245 | 1 | 0 | |a MICROSOFT CERTIFIED AZURE DATA FUNDAMENTALS (EXAM DP-900) CERTIFICATION GUIDE |h [electronic resource] : |b the comprehensive guide to passing the DP-900 exam on your first attempt / |c Marcelo Leite. |
| 260 | |a [S.l.] : |b PACKT PUBLISHING LIMITED, |c 2022. | ||
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| 520 | |a 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. | ||
| 505 | 0 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
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