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Amazon Redshift Cookbook

You're reading from Amazon Redshift Cookbook Recipes for building modern data warehousing solutions

Product type Paperback

Published in Apr 2025

Publisher Packt

ISBN-13 9781836206910

Length 468 pages

Edition 2nd Edition

Concepts

Data Science

Authors (3):

Shruti Worlikar

Patel

Anusha Challa

View More author details

Table of Contents (16) Chapters

Preface

1. Getting Started with Amazon Redshift FREE CHAPTER

2. Data Management

3. Loading and Unloading Data

4. Zero-ETL Ingestions

5. Scalable Data Orchestration for Automation

6. Platform Authorization and Security

7. Data Authorization and Security

8. Performance Optimization

9. Cost Optimization

10. Lakehouse Architecture

11. Data Sharing with Amazon Redshift

12. Generative AI and ML with Amazon Redshift

13. Other Books You May Enjoy

14. Index

Appendix

Implementing dynamic data masking

Dynamic data masking (DDM) (https://docs.aws.amazon.com/redshift/latest/dg/t_ddm.html) lets you hide sensitive data. It is often used to meet regulations or privacy standards. DDM allows you to control how sensitive data is displayed, based on a user’s permissions. This is done at the time the data is accessed, not when it is stored. DDM is an alternative to permanently obscuring the data during the data loading process. With DDM, you don’t need to modify your data pipelines. You set up masking policies that determine who can see what data. These policies are attached to tables and columns. The policies apply to individual users, roles, or everyone. DDM makes it easier to adapt to changing privacy requirements, without needing to change your data transformations, underlying data, or application queries.

Using DDM and Amazon Redshift Lambda User-Defined Functions (https://docs.aws.amazon.com/redshift/latest/dg/udf-creating-a-lambda...

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Authors (3)

Shruti Worlikar

Shruti Worlikar

Shruti Worlikar is a cloud professional with technical expertise in data lakes and analytics across cloud platforms. Her background has led her to become an expert in on-premises-to-cloud migrations and building cloud-based scalable analytics applications. Shruti earned her bachelor's degree in electronics and telecommunications from Mumbai University in 2009 and later earned her masters' degree in telecommunications and network management from Syracuse University in 2011. Her work history includes work at J.P. Morgan Chase, MicroStrategy, and Amazon Web Services (AWS). She is currently working in the role of Manager, Analytics Specialist SA at AWS, helping customers to solve real-world analytics business challenges with cloud solutions and working with service teams to deliver real value. Shruti is the DC Chapter Director for the non-profit Women in Big Data (WiBD) and engages with chapter members to build technical and business skills to support their career advancements. Originally from Mumbai, India, Shruti currently resides in Aldie, VA, with her husband and two kids.

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Patel

Patel

Harshida Patel is a senior analytics specialist solution architect at AWS, enabling customers to build scalable data lake and data warehousing applications using AWS analytical services. She has presented Amazon Redshift deep-dive sessions at re:Invent. Harshida has a bachelor's degree in electronics engineering and a master's in electrical and telecommunication engineering. She has over 15 years of experience architecting and building end-to-end data pipelines in the data management space. In the past, Harshida has worked in the insurance and telecommunication industries. She enjoys traveling and spending quality time with friends and family, and she lives in Virginia with her husband and son.

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Anusha Challa

Anusha Challa

Anusha Challa is a seasoned professional with over 15 years of expertise in architecting data and analytics solutions across on-premises and cloud environments. She has provided guidance to hundreds of Amazon Redshift customers, empowering them to design scalable and robust end-to-end data warehouse architectures. Anusha speaks at various AWS events, such as re:Invent and AWS Summits, where she shares best practices for using Amazon Redshift and other AWS analytics services. She has a bachelor's degree in computer science and a master's degree with a specialization in Machine Learning. Based in Chicago, Anusha enjoys reading books and traveling during her free time.

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