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208830095
Data Engineering with AWS: A practical guide to building scalable and secure enterprise data platforms (English Edition)
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Item #:
208830095
XPF 6695
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By the end of this book, you will be able to design and build scalable, secure, and cost-effective data platforms on AWS.
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What Stands Out
Comprehensive AWS Coverage
This guide provides in-depth insights into AWS services essential for data engineering, equipping users with practical knowledge to build scalable data platforms tailored to enterprise needs.
Hands-On Approach
Engage in practical exercises that foster real-world application of data engineering principles, ensuring that readers can effectively implement learned skills in their professional settings.
Security Focus
Emphasizing security, this book addresses critical protocols and best practices to safeguard data integrity, making it indispensable for organizations prioritizing secure data handling.
Product Details
- Data engineering and AWS form the backbone of modern enterprise data architecture, enabling organizations to harness the exponential growth of data for competitive advantage. As businesses generate petabytes of information daily, the ability to build scalable, secure, and cost-effective data platforms has become critical for survival in today's data-driven economy.This comprehensive guide takes you through the complete journey of building enterprise-grade data platforms on AWS. You will understand data lake foundations with S3, implement real-time streaming with Kinesis, and optimize batch processing using Glue. The book covers advanced topics, including data warehouse engineering with Redshift, modern architectural patterns like data mesh, and cross-boundary data sharing strategies. The guide explores the GenAI revolution transforming data platforms from human-centric to AI-native systems, covering enhanced medallion architectures that serve both traditional analytics and generative AI workloads.By the end of this book, you will be able to design and build scalable, secure, and cost-effective data platforms on AWS. You will master the skills to process massive datasets, implement enterprise-grade security, and architect solutions for real-time analytics and ML workflows, ultimately driving significant business value.What you will learn● Build petabyte-scale data lakes using S3 and Lake Formation.● Implement real-time streaming pipelines with Kinesis and Lambda.● Design cost-optimized data warehouses using Amazon Redshift.● Create modern data mesh architectures on AWS.● Master DataOps practices with CI/CD and IaC.● Architect GenAI-native platforms with enhanced medallion architectures.● Integrate ML pipelines using SageMaker and Glue.● Implement enterprise security and governance strategies.Who this book is forThis book is ideal for data engineers, cloud architects, DevOps engineers, and solutions architects building data platforms on AWS. Data scientists, ML engineers, and technical managers seeking to understand modern data infrastructure implementation will also find immense value.Table of Contents1. Modern Data Engineering Landscape2. Building Data Lake Foundations3. Data Formats and Storage Optimization4. Real-time Data Ingestion and Streaming5. Batch Data Processing6. Data Transformation and Quality7. Data Warehouse Engineering with Redshift8. Modern Data Architecture Patterns9. Data Governance and Security10. Cross-boundary Data Sharing and Collaborations11. Analytics and Visualization12. Machine Learning Integration13. DataOps and Automation14. GenAI Revolution in Data Engineering15. Future-Proofing Data PlatformsAppendix: Performance Tuning Guide
| Publisher | BPB Publications |
| Publication date | 28 Aug. 2025 |
| Language | English |
| Print length | 446 pages |
| ISBN-10 | 9365890969 |
| ISBN-13 | 978-9365890969 |
| Dimensions | 21.59 x 2.57 x 27.94 cm |
Who Should Buy?
-
Data Engineers
Ideal for data engineers looking to design and implement robust data platforms using AWS services effectively.
-
Cloud Architects
Beneficial for architects wanting to build scalable and secure data architectures aligned with enterprise requirements.
-
Business Analysts
Useful for analysts aiming to leverage AWS tools for better data management and analysis within enterprises.
-
Beginners in IT
May not suit individuals completely new to IT or lacking foundational knowledge in data engineering concepts.
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English edition Sanjiv Kumar Jha Format: Paperback Editorial Review
Data Engineering With AWS A Practical Guide To Building Scalable And Secure Enterprise Data Platforms English Edition is a comprehensive resource published by BPB Publications. This guide details effective strategies for constructing secure and scalable data architecture tailored for institutional needs. Spanning 446 pages, the book provides in-depth insights into leveraging AWS for data engineering, making it an essential read for professionals aiming to enhance their data platforms. With its clear language and structured format, readers can easily grasp complex topics, thus fostering better understanding and implementation. The publication date of 28 Aug 2025 ensures that the content remains relevant to current industry standards.
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Pros
- Comprehensive guide for AWS data engineering
- In-depth insights on scalable data platforms
- Structured format aids in understanding complex topics
- Ideal for professionals in data management
- English edition ensures wide accessibility
Cons
- Print length may be overwhelming for some readers
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Features & Benefits
- Learn to build petabyte-scale data lakes using S3 and Lake Formation.
- Implement real-time streaming pipelines with Kinesis and Lambda.
- Design cost-optimized data warehouses with Redshift.
- Master modern data mesh architectures and DataOps practices.
- Integrate machine learning pipelines using SageMaker and Glue.
- Achieve enterprise security and governance strategies for your data platforms.
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