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Ultimate AWS Data Engineering - Design Implement and Optimize Scalable Data Solutions on AWS with Practical Workflows and Visual Aids for Unmatched Impact - cover

Ultimate AWS Data Engineering - Design Implement and Optimize Scalable Data Solutions on AWS with Practical Workflows and Visual Aids for Unmatched Impact

Rathish Mohan

Publisher: Orange Education Pvt. Ltd

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Summary

Unlock the Power of AWS Data Engineering and Build Smarter Pipelines for Data-Driven Success.
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.
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
Available since: 01/23/2025.

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