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Subrat SaurabhAuthor of Kuch Woh Pal
Data Engineering Fundamentals: A Step-by-Step Approach
In today’s data-driven world, the ability to design, build, and manage robust data systems has become an essential skill. Data Engineering Fundamentals: A Step-by-Step Approach offers a clear and practical roadmap for anyone eager to understand how data truly powers modern businesses.
Written in an easy-to-follow style, this book demystifies complex data engineering concepts through real-world examples, visual explanations, and hands-on exercises. From data collection and storage to processing, transformation, and orchestration, readers will learn how to construct efficient, scalable, and reliable data pipelines from the ground up.
Each chapter builds on the last, guiding readers through essential tools and technologies such as SQL, ETL workflows, cloud platforms, and data modeling—without overwhelming jargon or assumptions of prior expertise.
Whether you’re a student exploring the data landscape, a professional transitioning into data roles, or an analyst seeking to expand your technical foundation, this book provides the structured learning path you need to succeed.
Data Engineering Fundamentals transforms theory into action, helping you develop the mindset and skills to build data systems that make information accessible, valuable, and insightful.
Discover how modern data infrastructure works—and how you can become the engineer who makes it all possible.
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Sandeep Kumar Pandey
"Data Engineering: A Practical Approach" is the ultimate guide for aspiring data engineers, software engineers, and professionals looking to elevate their skills in building, managing, and optimizing scalable data pipelines. This comprehensive book takes readers on a journey through the core principles of data engineering, emphasizing both theoretical understanding and practical application.
Through hands-on examples and real-world use cases, readers will learn to harness the power of cloud technologies like Azure Data Lake Storage (ADLS), Azure Data Factory (ADF), Azure Synapse Analytics, and Azure Databricks. Whether you're a beginner or have some foundational knowledge of data engineering, this book provides the knowledge needed to design efficient data architectures, implement ETL processes, ensure data quality and governance, and optimize data pipelines for maximum performance.
Key topics include:
The fundamentals of data modeling and database design
Building ETL pipelines using ADF and Databricks
Data warehousing, integration, and ingestion strategies
Ensuring data quality and governance with Azure Purview
Optimizing data pipelines for scalability and performance
Securing data through encryption, RBAC, and compliance best practices
This book blends theory with practical examples to ensure that readers can immediately apply their new knowledge to real-world scenarios. By the end of the book, you will be equipped with the tools and techniques to solve complex data engineering challenges and build robust, scalable solutions.
Author Biography: Sandeep Pandey
Sandeep Pandey is a seasoned data engineer and technology enthusiast with extensive experience in building and optimizing data pipelines, cloud architectures, and enterprise data solutions. Over the years, Sandeep has worked with a diverse range of industries, helping organizations harness the power of data to drive smarter decision-making and unlock new opportunities for growth.
With a passion for teaching and mentoring, Sandeep has created this book to share his deep knowledge of data engineering with software engineers, students, and professionals looking to upskill. His hands-on approach, combined with real-world examples, ensures that complex concepts are presented in a way that is accessible to both beginners and those with some data engineering background.
