Alex N. Azure Data Engineer Associate Certification Guide 2022 torrent

Textbook in PDF format

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.
Azure Basics
Introducing Azure Basics
Technical requirements
viii Table of Contents
Data Storage
Designing a Data Storage Structure Technical requirements
Designing a Partition Strategy Understanding the basics of partitioning
Designing the Serving Layer Technical requirements
Implementing Physical Data Storage Structures Technical requirements
Implementing Logical Data Structures Technical requirements
Implementing the Serving Layer Technical requirements
Design and Develop Data Processing (25-30%)
Ingesting and Transforming Data Technical requirements
Designing and Developing a Batch Processing Solution Technical requirements
Designing and Developing a Stream Processing Solution Technical requirements
Managing Batches and Pipelines Technical requirements
Design and Implement Data Security (10-15%)
Designing Security for Data Policies and Standards Technical requirements
Monitor and Optimize Data Storage and Data Processing (10-15%)
Monitoring Data Storage and Data Processing Technical requirements
Optimizing and Troubleshooting Data Storage and Data Processing
Practice Exercises
Sample Questions with Solutions
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