Ultimate AWS Data Engineering: Design, Implement and Optimize Scalable Data Solutions on AWS with Practical Workflows and Visual Aids for Unmatched ... (AWS Cloud Data Engineer — Professional Path) - Softcover

Mohan, Rathish; Agrawal, Shekhar; Chippada, Srinivasa Sunil; AVA, Orange

Softcover

ISBN 10: 9348107941 ISBN 13: 9789348107947

Publisher: Orange Education Pvt Ltd, 2025

Synopsis

Unlock the Power of AWS Data Engineering and Build Smarter Pipelines for Data-Driven Success.

Accelerate your cloud career with the ultimate AWS data engineering guide. This book is crafted to help both beginners and professionals design scalable data pipelines on AWS and implement robust cloud data solutions using proven strategies and practical workflows.

Book Description

In 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.

What You’ll Gain from This Guide:

• Efficient strategies to optimize big data workflows in AWS cloud, ensuring cost-effective and fault-tolerant results.
• Step-by-step instructions for practical AWS data engineering for beginners, making complex concepts easy to grasp.
• Real-world examples of AWS ETL pipelines and data transformation workflows to handle large-scale operations.
• Detailed methods on integrating AWS Redshift and DynamoDB for unified, scalable architectures.
• Blueprints for end-to-end data architecture on AWS, from planning to deployment.
• Simplified guides to cloud data engineering AWS and best practices for storage, partitioning, and sharding.
• Practical solutions and troubleshooting for building resilient and cost-effective AWS pipelines across diverse use cases.

Why Your Team Will Benefit:

• Gain hands-on insights for scalable AWS data pipelines and real value for cloud data solutions.
• Learn how to optimize, replicate, and partition data using industry-standard AWS architecture.
• Unlock effective approaches to AWS data replication, fault-tolerant pipelines, and more—all with clear, actionable direction.
• All guidance aligns with the latest, authentic cloud technology trends and avoids any misuse of trademarked or copyrighted content.

This book enables you to master data engineering AWS, AWS scalable solutions, and the fundamentals of cloud data transformation. Written in a simple, approachable tone for maximum reader benefit, every detail matches the latest AWS practices and ensures authenticity for your listing.

Unlock your potential—start building scalable, resilient, and high-impact AWS data solutions today!

Table of Contents
1. Unveiling the Secrets of Data Engineering
2. Architecting for Scalability: Data Replication Techniques
3. Partitioning and Sharding: Optimizing Data Management
4. Ensuring Consistency: Consensus Mechanisms and Models
5. Balancing the Load: Achieving Performance and Efficiency
6. Building Fault-Tolerant Architectures
7. Exploring the Realm of AWS Data Storage Services
8. Orchestrating Data Flow
9. Advanced Data Pipelines and Transformation
10. Data Warehousing Demystified
11. Visualizing the Unseen
12. AWS Machine Learning: Classic AI to Generative AI
13. Advanced Data Engineering with AWS
Index

Edition details

• Publisher: Orange Education Pvt Ltd
• Publication date: 2025
• Language: English
• ISBN 10: 9348107941
• ISBN 13: 9789348107947
• Binding: Paperback
• Number of pages: 300