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 3: Designing a Partition Strategy

Data partitioning refers to the process of dividing data and storing it in physically different locations. We partition data mainly for performance, scalability, manageability, and security reasons. Partitioning itself is a generic term, but the methods and techniques of partitioning vary from service to service—for example, the partitioning techniques used for Azure Blob storage might not be the same as those applied for database services such as Azure SQL or Azure Synapse Dedicated SQL pool. Similarly, document databases such as Cosmos DB have different partitioning techniques from Azure Queues or Azure Tables. In this chapter, we will explore some of the important partitioning techniques and when to use them.

As in the previous chapter, we will again be focusing more on the design aspects, as per the syllabus. The implementation details will be covered in Chapter 5, Implementing Physical Data Storage Structures.

This chapter...