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

Exploring Azure data services for modern data warehouses

When we think of modern data warehouse architecture, we think of the process consisting of data analytics, which can be summarized in the following phases:

  1. Data ingestion and preparation (ELT)
  2. Making data ready for consumption (modeling)
  3. Providing access to this data (reporting or API connections)

In this chapter, we will explore the possibilities of services that Azure offers to implement these phases. In Chapter 12, Provisioning and Configuring Large-Scale Data Analytics in Azure, there is a hands-on exercise that will help us understand in practice phases 1 and 2, and then in Chapter 13, Working with Power BI, we will explore Power BI for reporting.

Let’s start with data ingestion and preparation.

Data ingestion and preparation (ELT/ETL)

ELT stands for extract, load, and transform, and ETL (as mentioned earlier) stands for extract, transform, and load. These reflect the process of data...