Discover the world of data engineering in an on-premises setting versus the Azure cloud
Key Features
● Explore Azure data engineering from foundational concepts to advanced techniques, spanning SQL databases, ETL processes, and cloud-native solutions.
● Learn to implement real-world data projects with Azure services, covering data integration, storage, and analytics, tailored for diverse business needs.
● Prepare effectively for Azure data engineering certifications with detailed exam-focused content and practical exercises to reinforce learning.
Book Description
Embark on a comprehensive journey into Azure data engineering with
“Ultimate Azure Data Engineering” . Starting with foundational topics like SQL and relational database concepts, you’ll progress to comparing data engineering practices in Azure versus on-premises environments. Next, you will dive deep into Azure cloud fundamentals, learning how to effectively manage heterogeneous data sources and implement robust Extract, Transform, Load (ETL) concepts using Azure Data Factory, mastering the orchestration of data workflows and pipeline automation.
The book then moves to explore advanced database design strategies and discover best practices for optimizing data performance and ensuring stringent data security measures. You will learn to visualize data insights using Power BI and apply these skills to real-world scenarios. Whether you’re aiming to excel in your current role or preparing for Azure data engineering certifications, this book equips you with practical knowledge and hands-on expertise to thrive in the dynamic field of Azure data engineering.
What you will learn
● Master the core principles and methodologies that drive data engineering such as data processing, storage, and management techniques.
● Gain a deep understanding of Structured Query Language (SQL) and relational database management systems (RDBMS) for Azure Data Engineering.
● Learn about Azure cloud services for data engineering, such as Azure SQL Database, Azure Data Factory, Azure Synapse Analytics, and Azure Blob Storage.
● Gain proficiency to orchestrate data workflows, schedule data pipelines, and monitor data integration processes across cloud and hybrid environments.
● Design optimized database structures and data models tailored for performance and scalability in Azure.
● Implement techniques to optimize data performance such as query optimization, caching strategies, and resource utilization monitoring.
● Learn how to visualize data insights effectively using tools like Power BI to create interactive dashboards and derive data-driven insights.
Table of Contents
1. Introduction to Data Engineering
2. Understanding SQL and RDBMS Concepts
3. Data Engineering: Azure Versus On-Premises
4. Azure Cloud Concepts
5. Working with Heterogenous Data Sources
6. ETL Concepts
7. Database Design and Modeling
8. Performance Best Practices and Data Security
9. Data Visualization and Application in Real World
10. Data Engineering Certification Guide
Index
About the Authors
Ashish Agarwal currently works as an Engineering Architect in the Azure SQL Engineering team at Microsoft, where he works with large and complex SQL modernization projects spanning from SQL On-Premises to Azure Iaa S and Paa S Platforms.
He holds an Honors Bachelor’s degree in Computer Science Engineering from BMIT, Jaipur, Rajasthan, India, affiliated with Rajasthan Technical University, Kota, Rajasthan, India. He earned the title of Best Outgoing Student in Computer Science Engineering for his graduating batch. He has worked at top product-based companies, Fin Tech organizations, as well as large MNCs across various domains.
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