"It was a wonderful experience interacting with you and appreciate the way you have planned and executed the whole publication process within the agreed timelines.”
Subrat SaurabhAuthor of Kuch Woh Pal
Data Engineering Fundamental: A Step by Step Approach
Unlock the Power of Data with Practical Guidance from a Data Engineering Expert
In today’s data-driven world, organizations thrive on the ability to harness, process, and analyze data effectively. Data Engineering Fundamental: A Step by Step Approach is the ultimate guide for aspiring data engineers, data analysts, and professionals seeking to build a robust foundation in data engineering.
This comprehensive book breaks down the core concepts of data engineering, offering a practical, hands-on approach to mastering key tools and techniques. From data pipelines and ETL processes to cloud technologies and database optimization, you’ll explore a wide range of topics essential for managing and transforming data at scale.
Key features include:
Real-World Case Studies: Apply your learning to scenarios faced by data engineers in leading industries.
Step-by-Step Guides: Detailed instructions to walk you through complex data engineering processes.
Tool Mastery: In-depth coverage of popular platforms such as AWS, Azure, Databricks, and SQL databases.
Best Practices: Learn how to design, optimize, and maintain efficient data pipelines.
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.
