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 data ingestion and processing

The process of obtaining and importing raw data for immediate use, processing, or storage is known as data ingestion.

To build an analytical environment, we use data ingestion techniques to copy data from sources and store it within a data lake or an analytical database; this process is called a data pipeline.

Data ingestion pipelines are composed of one or more steps of data processing, that is, a dataset of the data source is captured and processed, and then the output dataset is generated.

Data pipelines

Data pipelines load and process data through connected services, allowing you to select the best technology for each phase of the workflow.

For example, in Azure, you can use a SQL Server as a data source, then use Azure SQL Database to run a store procedure that searches for data values, and then run a processing routine with Azure Databricks by applying a custom data model. All of these are steps in a data pipeline.

Data...