Ultimate AWS Data Engineering

Unlock the Power of AWS Data Engineering and Build Smarter Pipelines for Data-Driven Success.
Key Features● Gain an in-depth understanding of essential AWS services such as S3, DynamoDB, Redshift, and Glue to build scalable data solutions.● Learn to design efficient, fault-tolerant data pipelines while adhering to best practices in cost management and security.
Book DescriptionIn today’s data-driven era, mastering AWS data engineering is key to building scalable, secure pipelines that drive innovation and decision-making. Ultimate AWS Data Engineering is your comprehensive guide to mastering the art of building robust, cost-effective, and fault-tolerant data pipelines on AWS. Designed for data professionals and enthusiasts, this book begins with foundational concepts and progressively explores advanced techniques, equipping you with the skills to tackle real-world challenges.
Throughout the chapters, you’ll dive deep into the core principles of data replication, partitioning, and load balancing, while gaining hands-on experience with AWS services like S3, DynamoDB, Redshift, and Glue. Learn to design resilient data architectures, optimize performance, and ensure seamless data transformation—all while adhering to best practices in cost-efficiency and security.
Whether you aim to streamline your organization’s data flow, enhance your cloud expertise, or future-proof your career in data engineering, this comprehensive guide offers the practical knowledge and insights you need to succeed. By the end, you will be ready to craft impactful, data-driven solutions on AWS with confidence and expertise.
What you will learn● Design scalable data pipelines using core AWS data engineering tools.● Master data replication, partitioning, and sharding techniques on AWS.● Build fault-tolerant architectures with AWS scalability and reliability.
Table of Contents1. Unveiling the Secrets of Data Engineering2. Architecting for Scalability: Data Replication Techniques3. Partitioning and Sharding: Optimizing Data Management4. Ensuring Consistency: Consensus Mechanisms and Models5. Balancing the Load: Achieving Performance and Efficiency6. Building Fault-Tolerant Architectures7. Exploring the Realm of AWS Data Storage Services8. Orchestrating Data Flow9. Advanced Data Pipelines and Transformation10. Data Warehousing Demystified11. Visualizing the Unseen12. AWS Machine Learning: Classic AI to Generative AI13. Advanced Data Engineering with AWS.