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AWS Certified Solutions Architect - Associate (SAA-C03) Exam Guide

You're reading from   AWS Certified Solutions Architect - Associate (SAA-C03) Exam Guide Aligned with the latest AWS SAA-C03 exam objectives to help you pass the exam on your first attempt

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Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781837630004
Length 500 pages
Edition 1st Edition
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Authors (2):
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Michelle Chismon Michelle Chismon
Author Profile Icon Michelle Chismon
Michelle Chismon
Kate Gawron Kate Gawron
Author Profile Icon Kate Gawron
Kate Gawron
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Table of Contents (18) Chapters Close

Preface 1. Chapter 1: Understanding Cloud Fundamentals 2. Chapter 2: Virtual Private Cloud FREE CHAPTER 3. Chapter 3: Identity and Access Management 4. Chapter 4: Compute 5. Chapter 5: Storage 6. Chapter 6: DNS and Load Balancing 7. Chapter 7: Data and Analytics 8. Chapter 8: Migrations and Data Transfer 9. Chapter 9: Serverless and Application Integration 10. Chapter 10: Security 11. Chapter 11: Management and Governance 12. Chapter 12: Design Secure Architectures 13. Chapter 13: Design Resilient Architectures 14. Chapter 14: Design High-Performing Architectures 15. Chapter 15: Design Cost-Optimized Architectures 16. Chapter 16: Accessing the Online Practice Resources 17. Other Books You May Enjoy

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Analytics on AWS is an extremely wide range of tools and services to help organizations collect, store, process, and analyze data. AWS offers solutions for data lakes, data warehousing, real-time analytics, and machine learning. This helps businesses turn raw data into useful insights for better decision-making and innovation. With services such as Amazon Redshift, Amazon Athena, AWS Glue, and Amazon QuickSight, AWS makes it easy to work with different types of data, run complex queries, and create reports.

Amazon Redshift

Amazon Redshift is a fully managed, petabyte-scale data warehouse service designed for high-performance analysis of structured and semi-structured data. It enables organizations to run complex analytic queries against massive datasets, using familiar SQL-based tools and business intelligence (BI) applications. Common use cases include BI, predictive analytics, and big data processing, so it is used by many companies that need to analyze large...

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