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

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

Symbols

360-degree customer view case study 65, 66

consolidated view, of customer data 66

A

access control lists (ACLs) 172

ACID properties

atomicity 15

consistency 15

durability 16

isolation 15

American National Standards Institute (ANSI) 40

analytical database 9, 71-73

data ingestion 10

data processing 10

data query 10

example 10, 11

analytical data model 73, 77

dimensions 78, 79

exploring 77, 78

facts 78

analytical data store 73

data lake 76

data warehouse 76

exploring 76

hybrid approaches 77

analytical workload 17, 18

Apache Hadoop 180

Apache HBase 180

Apache Interactive Query 180

Apache Kafka 180

Apache Spark 180

Apache Spark Pool 188

Apache Spark Stream 193

Apache Storm 180

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