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

Chapter 5: Implementing Physical Data Storage Structures

Hope you have had a good learning experience up till now. Let's continue our journey toward certification with more interesting topics in this chapter. Till the previous chapter, we have been focusing on the design aspects, but from now on, we will be focusing on the implementation details. We will learn how to implement the storage-level concepts that we learned in the previous chapters. Once you complete this chapter, you should be able to decide on and implement the following: what kind of data sharding is required, when to compress your data, how many partitions to create, what kind of data redundancy to maintain, and so on.

We will cover the following topics in this chapter:

  • Getting started with Azure Synapse Analytics
  • Implementing compression
  • Implementing partitioning
  • Implementing horizontal partitioning or sharding
  • Implementing distributions
  • Implementing different table geometries with...