-
Book Overview & Buying
-
Table Of Contents
Azure Data Engineer Associate Certification Guide
By :
Azure Data Engineer Associate Certification Guide
By:
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)
Preface
Part 1: Azure Basics
Free Chapter
Chapter 1: Introducing Azure Basics
Part 2: Data Storage
Chapter 2: Designing a Data Storage Structure
Chapter 3: Designing a Partition Strategy
Chapter 4: Designing the Serving Layer
Chapter 5: Implementing Physical Data Storage Structures
Chapter 6: Implementing Logical Data Structures
Chapter 7: Implementing the Serving Layer
Part 3: Design and Develop Data Processing (25-30%)
Chapter 8: Ingesting and Transforming Data
Chapter 9: Designing and Developing a Batch Processing Solution
Chapter 10: Designing and Developing a Stream Processing Solution
Chapter 11: Managing Batches and Pipelines
Part 4: Design and Implement Data Security (10-15%)
Chapter 12: Designing Security for Data Policies and Standards
Part 5: Monitor and Optimize Data Storage and Data Processing (10-15%)
Chapter 13: Monitoring Data Storage and Data Processing
Chapter 14: Optimizing and Troubleshooting Data Storage and Data Processing
Part 6: Practice Exercises
Chapter 15: Sample Questions with Solutions
Other Books You May Enjoy
