Amazon Redshift The Definitive Guide Jump Start Analytics Using Cloud Data Warehousing 1st Edition Rajesh Francis, Rajiv Gupta, Milind Oke – Ebook PDF Instant Download/Delivery ISBN(s): 9781098135263, 1098135261
Product details:
- ISBN 10: 1098135261
- ISBN 13: 9781098135263
- Author: Rajesh Francis, Rajiv Gupta, Milind Oke
Amazon Redshift powers analytic cloud data warehouses worldwide, from startups to some of the largest enterprise data warehouses available today. This practical guide thoroughly examines this managed service and demonstrates how you can use it to extract value from your data immediately, rather than go through the heavy lifting required to run a typical data warehouse. Analytic specialists Rajesh Francis, Rajiv Gupta, and Milind Oke detail Amazon Redshift’s underlying mechanisms and options to help you explore out-of-the box automation. Whether you’re a data engineer who wants to learn the art of the possible or a DBA looking to take advantage of machine learning-based auto-tuning, this book helps you get the most value from Amazon Redshift. By understanding Amazon Redshift features, you’ll achieve excellent analytic performance at the best price, with the least effort. This book helps you: Build a cloud data strategy around Amazon Redshift as foundational data warehouse Get started with Amazon Redshift with simple-to-use data models and design best practices Understand how and when to use Redshift Serverless and Redshift provisioned clusters Take advantage of auto-tuning options inherent in Amazon Redshift and understand manual tuning options Transform your data platform for predictive analytics using Redshift ML and break silos using data sharing Learn best practices for security, monitoring, resilience, and disaster recovery Leverage Amazon Redshift integration with other AWS services to unlock additional value
Table contents:
1. AWS for Data
2. Getting Started with Amazon Redshift
3. Setting Up Your Data Models and Ingesting Data
4. Data Transformation Strategies
5. Scaling and Performance Optimizations
6. Amazon Redshift Machine Learning
7. Collaboration with Data Sharing
8. Securing and Governing Data
9. Migrating to Amazon Redshift
10. Monitoring and Administration
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