Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Modern Data Architecture on AWS

You're reading from   Modern Data Architecture on AWS A Practical Guide for Building Next-Gen Data Platforms on AWS

Arrow left icon
Product type Paperback
Published in Aug 2023
Publisher Packt
ISBN-13 9781801813396
Length 420 pages
Edition 1st Edition
Tools
Arrow right icon
Author (1):
Arrow left icon
Behram Irani Behram Irani
Author Profile Icon Behram Irani
Behram Irani
Arrow right icon
View More author details
Toc

Table of Contents (24) Chapters Close

Preface 1. Part 1: Foundational Data Lake
2. Prologue: The Data and Analytics Journey So Far FREE CHAPTER 3. Chapter 1: Modern Data Architecture on AWS 4. Chapter 2: Scalable Data Lakes 5. Part 2: Purpose-Built Services And Unified Data Access
6. Chapter 3: Batch Data Ingestion 7. Chapter 4: Streaming Data Ingestion 8. Chapter 5: Data Processing 9. Chapter 6: Interactive Analytics 10. Chapter 7: Data Warehousing 11. Chapter 8: Data Sharing 12. Chapter 9: Data Federation 13. Chapter 10: Predictive Analytics 14. Chapter 11: Generative AI 15. Chapter 12: Operational Analytics 16. Chapter 13: Business Intelligence 17. Part 3: Govern, Scale, Optimize And Operationalize
18. Chapter 14: Data Governance 19. Chapter 15: Data Mesh 20. Chapter 16: Performant and Cost-Effective Data Platform 21. Chapter 17: Automate, Operationalize, and Monetize 22. Index 23. Other Books You May Enjoy

Data ingestion patterns

One of the most complex and time-consuming parts of data warehouse modernization is data onboarding. Data can be onboarded in many different ways, using many different services. It all boils down to the requirement and the need for onboarding data in a particular manner. Let’s explore some typical data onboarding patterns for Amazon Redshift.

Data ingestion using AWS DMS

Let’s start with a use case first, so that the importance of DMS can be better understood when it comes to loading data into Redshift.

Use case for batch loading data into Amazon Redshift

GreatFin uses multiple databases and traditional data warehouses for their enterprise analytics reporting needs. They want to modernize their data warehouse using Amazon Redshift and would like to bulk load all the historic data from these existing systems into Redshift. They are looking for a fast, easy, and cost-effective way to do this in Redshift.

As you may recall from our...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image