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Amazon Redshift Cookbook

You're reading from  Amazon Redshift Cookbook

Product type Book
Published in Jul 2021
Publisher Packt
ISBN-13 9781800569683
Pages 384 pages
Edition 1st Edition
Languages
Concepts
Authors (3):
Shruti Worlikar Shruti Worlikar
Profile icon Shruti Worlikar
LinkedIn
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.
See other products by Shruti Worlikar
Thiyagarajan Arumugam Thiyagarajan Arumugam
Profile icon Thiyagarajan Arumugam
LinkedIn
Thiyagarajan Arumugam (Thiyagu) is a principal big data solution architect at AWS, architecting and building solutions at scale using big data to enable data-driven decisions. Prior to AWS, Thiyagu as a data engineer built big data solutions at Amazon, operating some of the largest data warehouses and migrating to and managing them. He has worked on automated data pipelines and built data lake-based platforms to manage data at scale for the customers of his data science and business analyst teams. Thiyagu is a certified AWS Solution Architect (Professional), earned his master's degree in mechanical engineering at the Indian Institute of Technology, Delhi, and is the author of several blog posts at AWS on big data. Thiyagu enjoys everything outdoors – running, cycling, ultimate frisbee – and is currently learning to play the Indian classical drum the mrudangam. Thiyagu currently resides in Austin, TX, with his wife and two kids.
See other products by Thiyagarajan Arumugam
Harshida Patel Harshida Patel
Profile icon Harshida Patel
LinkedIn
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.
See other products by Harshida Patel
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Table of Contents (13) Chapters

Preface 1. Chapter 1: Getting Started with Amazon Redshift 2. Chapter 2: Data Management 3. Chapter 3: Loading and Unloading Data 4. Chapter 4: Data Pipelines 5. Chapter 5: Scalable Data Orchestration for Automation 6. Chapter 6: Data Authorization and Security 7. Chapter 7: Performance Optimization 8. Chapter 8: Cost Optimization 9. Chapter 9: Lake House Architecture 10. Chapter 10: Extending Redshift's Capabilities 11. Other Books You May Enjoy Appendix

Exporting a data lake from Amazon Redshift

Amazon Redshift empowers a lake house architecture, allowing you to query data within the data warehouse and data lake using Amazon Redshift Spectrum and also to export your data back to the data lake on Amazon S3, to be used by other analytical and ML services. You can store data in open file formats in your Amazon S3 data lake when performing the data lake export to integrate with your existing data lake formats.

Getting ready

To complete this recipe, you will need the following to be set up:

  • An IAM user with access to Amazon Redshift
  • An Amazon Redshift cluster deployed in the eu-west-1 AWS Region with the retail dataset created from Chapter 3, Loading and Unloading Data, using the Loading data from Amazon S3 using COPY recipe
  • Amazon Redshift cluster masteruser credentials
  • Access to any SQL interface such as a SQL client or the Amazon Redshift Query Editor
  • An AWS account number—we will refer to this in...
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Authors (3)

Left arrow icon
Profile icon Shruti Worlikar
LinkedIn
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.
Read more
See other products by Shruti Worlikar
Profile icon Thiyagarajan Arumugam
LinkedIn
Thiyagarajan Arumugam (Thiyagu) is a principal big data solution architect at AWS, architecting and building solutions at scale using big data to enable data-driven decisions. Prior to AWS, Thiyagu as a data engineer built big data solutions at Amazon, operating some of the largest data warehouses and migrating to and managing them. He has worked on automated data pipelines and built data lake-based platforms to manage data at scale for the customers of his data science and business analyst teams. Thiyagu is a certified AWS Solution Architect (Professional), earned his master's degree in mechanical engineering at the Indian Institute of Technology, Delhi, and is the author of several blog posts at AWS on big data. Thiyagu enjoys everything outdoors – running, cycling, ultimate frisbee – and is currently learning to play the Indian classical drum the mrudangam. Thiyagu currently resides in Austin, TX, with his wife and two kids.
Read more
See other products by Thiyagarajan Arumugam
Profile icon Harshida Patel
LinkedIn
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.
Read more
See other products by Harshida Patel
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