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Exam AWS Certified Data Engineer - Associate DEA-C01 topic 1 question 134 discussion

Exam question from Amazon's AWS Certified Data Engineer - Associate DEA-C01
Question #: 134
Topic #: 1
[All AWS Certified Data Engineer - Associate DEA-C01 Questions]

A company ingests data from multiple data sources and stores the data in an Amazon S3 bucket. An AWS Glue extract, transform, and load (ETL) job transforms the data and writes the transformed data to an Amazon S3 based data lake. The company uses Amazon Athena to query the data that is in the data lake.

The company needs to identify matching records even when the records do not have a common unique identifier.

Which solution will meet this requirement?

  • A. Use Amazon Macie pattern matching as part of the ETL job.
  • B. Train and use the AWS Glue PySpark Filter class in the ETL job.
  • C. Partition tables and use the ETL job to partition the data on a unique identifier.
  • D. Train and use the AWS Lake Formation FindMatches transform in the ETL job.
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Suggested Answer: D 🗳️
by Shanmahi at Aug. 6, 2024, 7:52 a.m.
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Shanmahi
Highly Voted 8 months, 3 weeks ago
Selected Answer: D
AWS Lake Formation provides machine learning capabilities to create custom transforms to cleanse your data. There is currently one available transform named FindMatches. The FindMatches transform enables you to identify duplicate or matching records in your dataset, even when the records do not have a common unique identifier and no fields match exactly. This will not require writing any code or knowing how machine learning works.
upvoted 6 times
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RockyLeon
Most Recent 5 months ago
Selected Answer: D
Correct answer is D
upvoted 1 times
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LR2023
7 months ago
Selected Answer: D
upvoted 1 times
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