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

Regressing to a previous state

Regressing to a previous state or rolling back to a stable state is a very commonly used technique in databases and OLTP scenarios. In OLTP scenarios, the transformation instructions are grouped together into a transaction and if any of the instructions fail or reach an inconsistent state then the entire transaction rolls back. Although databases provide such functionality, we don't have such ready-made support in Azure Data Factory or Oozie (HDInsight) today. We will have to build our own rollback stages depending on the activity. Let's look at an example of how to do a rollback of a data copy activity in ADF.

ADF provides options for checking consistency and setting limits for fault tolerance. You can enable them in the Settings options of a copy activity as shown in the following screenshot.

Figure 9.30 – Enabling consistency verification and fault tolerance in an ADF copy activity

If the activity fails...