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Solutions Architect's Handbook

Solutions Architect's Handbook

By : Saurabh Shrivastava, Neelanjali Srivastav
4.7 (59)
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Solutions Architect's Handbook

Solutions Architect's Handbook

4.7 (59)
By: Saurabh Shrivastava, Neelanjali Srivastav

Overview of this book

Master the art of solution architecture and excel as a Solutions Architect with the Solutions Architect's Handbook. Authored by seasoned AWS technology leaders Saurabh Shrivastav and Neelanjali Srivastav, this book goes beyond traditional certification guides, offering in-depth insights and advanced techniques to meet the specific needs and challenges of solutions architects today. This edition introduces exciting new features that keep you at the forefront of this evolving field. Large language models, generative AI, and innovations in deep learning are cutting-edge advancements shaping the future of technology. Topics such as cloud-native architecture, data engineering architecture, cloud optimization, mainframe modernization, and building cost-efficient and secure architectures remain important in today's landscape. This book provides coverage of these emerging and key technologies and walks you through solution architecture design from key principles, providing you with the knowledge you need to succeed as a Solutions Architect. It will also level up your soft skills, providing career-accelerating techniques to help you get ahead. Unlock the potential of cutting-edge technologies, gain practical insights from real-world scenarios, and enhance your solution architecture skills with the Solutions Architect's Handbook.
Table of Contents (20 chapters)
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18
Other Books You May Enjoy
19
Index

Summary

In this chapter, you learned about the big data architecture and components for a big data pipeline design. You learned about data ingestion and various technology choices available to collect batch and stream data for processing. As the cloud is central to storing the vast amounts of data produced today, you learned about the various services available to ingest data in the AWS cloud ecosystem.

Data storage is one of the central points of handling big data. You learned about various kinds of data stores, including structured and unstructured data, NoSQL, and data warehousing, with the appropriate technology choices associated with each. You learned about cloud data storage from popular public cloud providers.

Once you collect and store data, you need to transform it to get insights into that data and visualize your business requirements. You learned about data processing architecture and technology choices to choose open source and cloud-based data processing tools...

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