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Serverless ETL and Analytics with AWS Glue

You're reading from   Serverless ETL and Analytics with AWS Glue Your comprehensive reference guide to learning about AWS Glue and its features

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Product type Paperback
Published in Aug 2022
Publisher Packt
ISBN-13 9781800564985
Length 434 pages
Edition 1st Edition
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Authors (6):
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Vishal Pathak Vishal Pathak
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Vishal Pathak
Ishan Gaur Ishan Gaur
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Ishan Gaur
Tomohiro Tanaka Tomohiro Tanaka
Author Profile Icon Tomohiro Tanaka
Tomohiro Tanaka
Albert Quiroga Albert Quiroga
Author Profile Icon Albert Quiroga
Albert Quiroga
Subramanya Vajiraya Subramanya Vajiraya
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Subramanya Vajiraya
Noritaka Sekiyama Noritaka Sekiyama
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Noritaka Sekiyama
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Table of Contents (20) Chapters Close

Preface 1. Section 1 – Introduction, Concepts, and the Basics of AWS Glue
2. Chapter 1: Data Management – Introduction and Concepts FREE CHAPTER 3. Chapter 2: Introduction to Important AWS Glue Features 4. Chapter 3: Data Ingestion 5. Section 2 – Data Preparation, Management, and Security
6. Chapter 4: Data Preparation 7. Chapter 5: Data Layouts 8. Chapter 6: Data Management 9. Chapter 7: Metadata Management 10. Chapter 8: Data Security 11. Chapter 9: Data Sharing 12. Chapter 10: Data Pipeline Management 13. Section 3 – Tuning, Monitoring, Data Lake Common Scenarios, and Interesting Edge Cases
14. Chapter 11: Monitoring 15. Chapter 12: Tuning, Debugging, and Troubleshooting 16. Chapter 13: Data Analysis 17. Chapter 14: Machine Learning Integration 18. Chapter 15: Architecting Data Lakes for Real-World Scenarios and Edge Cases 19. Other Books You May Enjoy

Deduplicating records

When you start analyzing the business data, you may find that it’s incorrect and that there are multiple different notations of the same record.

The following example table contains duplicates:

Figure 6.3 – Customer table with duplicates

As you may have noticed, there are only four unique records in the preceding table. Two records have two different notations, which causes duplication. If you analyze the data with these kinds of duplicated records, the result may include unexpected bias, so you will get an incorrect result.

With AWS Glue, you can use the FindMatches transform to find duplicated records. FindMatches is one of the ETL transforms provided in the Glue ETL library. With the FindMatches transform, you can match records and identify and remove duplicate records based on the ML model.

Let’s look at the end-to-end matching process:

  1. Register a table definition for your data in AWS Glue Data...
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