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

Summary

With that, we have come to the end of this small chapter. We started by learning how to trigger Batch loads, how to handle errors and validate Batch jobs, and then moved on to ADF and Synapse pipelines. We learned about setting up triggers, managing and monitoring pipelines, running Spark pipelines, and configuring version control in ADF and Synapse Pipelines. With all this knowledge, you should now be confident in creating and managing pipelines using ADF, Synapse Pipelines, and Azure Batch.

This chapter marks the end of the Designing and Developing Data Processing section, which accounts for about 25-30% of the certification goals. From the next chapter onward, we will next move on to the Designing and Implementing Data Security section, where we will be focusing on the security aspects of data processing.