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.

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Spis treści

Azure Data Engineer Associate Certification Guide. A hands-on reference guide to developing your data engineering skills and preparing for the DP-203 exam eBook -- spis treści

• 1. Introducing Azure Basics
• 2. Designing a Data Storage Structure
• 3. Designing a Partition Strategy
• 4. Designing the Serving Layer
• 5. Implementing Physical Data Storage Structures
• 6. Implementing Logical Data Structures
• 7. Implementing the Serving Layer
• 8. Ingesting and Transforming Data
• 9. Designing and Developing a Batch Processing Solution
• 10. Designing and Developing a Stream Processing Solution
• 11. Managing Batches and Pipelines
• 12. Designing Security for Data Policies and Standards
• 13. Monitoring Data Storage and Data Processing
• 14. Optimizing and Troubleshooting Data Storage and Data Processing
• 15. Sample Questions with Solutions