Book Image

Azure Data Engineer Associate Certification Guide

By : Newton Alex
Book Image

Azure Data Engineer Associate Certification Guide

By: Newton Alex

Overview of this book

Azure is one of the leading cloud providers in the world, providing numerous services for data hosting and data processing. Most of the companies today are either cloud-native or are migrating to the cloud much faster than ever. This has led to an explosion of data engineering jobs, with aspiring and experienced data engineers trying to outshine each other. Gaining the DP-203: Azure Data Engineer Associate certification is a sure-fire way of showing future employers that you have what it takes to become an Azure Data Engineer. This book will help you prepare for the DP-203 examination in a structured way, covering all the topics specified in the syllabus with detailed explanations and exam tips. The book starts by covering the fundamentals of Azure, and then takes the example of a hypothetical company and walks you through the various stages of building data engineering solutions. Throughout the chapters, you'll learn about the various Azure components involved in building the data systems and will explore them using a wide range of real-world use cases. Finally, you’ll work on sample questions and answers to familiarize yourself with the pattern of the exam. By the end of this Azure book, you'll have gained the confidence you need to pass the DP-203 exam with ease and land your dream job in data engineering.
Table of Contents (23 chapters)
1
Part 1: Azure Basics
3
Part 2: Data Storage
10
Part 3: Design and Develop Data Processing (25-30%)
15
Part 4: Design and Implement Data Security (10-15%)
17
Part 5: Monitor and Optimize Data Storage and Data Processing (10-15%)
20
Part 6: Practice Exercises

Managing data pipelines in Data Factory/Synapse pipelines

ADF and Synapse pipelines provide two tabs called Manage and Monitor, which can help us manage and monitor the pipelines, respectively.

In the Manage tab, you can add, edit, and delete linked services, integration runtimes, triggers, configure Git, and more, as shown in the following screenshot:

Figure 11.9 – The Manage screen of ADF

We have already learned about linked services throughout this book. Now, let's explore the topic of integration runtimes in ADF and Synapse pipelines.

Integration runtimes

An integration runtime (IR) refers to the compute infrastructure that's used by ADF and Synapse Pipelines to run data pipelines and data flows. These are the actual machines or VMs that run the job behind the scenes.

The IR takes care of running data flows, copying data across public and private networks, dispatching activities to services such as Azure HDInsight and Azure...