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

Learning the basics of data modeling and schemas

Data modeling is a process of designing how data will be represented in data stores. Many data modeling techniques were originally designed for databases and warehouses. Since the Serving layers are usually built with relational data stores such as data warehouses, some of the data modeling techniques can be applied for the Serving layer design too. But do remember that the Serving layer could be built using other storage technologies such as document databases, key-value stores, and so on, based on the customer requirements.

Unlike data lakes, in databases or data warehouses we don't have the luxury of storing huge volumes of data in the format we like. Databases and data warehouses can perform querying exceptionally fast, provided the data is stored in predetermined formats and is limited in size. Hence, while designing the Serving layer, we need to identify the specifics of which data needs to be stored, which format to store...