Exam AWS Certified Data Analytics - Specialty topic 1 question 156 discussion

Exam question from Amazon's AWS Certified Data Analytics - Specialty

Question #: 156
Topic #: 1

[All AWS Certified Data Analytics - Specialty Questions]

A healthcare company ingests patient data from multiple data sources and stores it in an Amazon S3 staging bucket. An AWS Glue ETL job transforms the data, which is written to an S3-based data lake to be queried using Amazon Athena. The company wants to match patient records even when the records do not have a common unique identifier.
Which solution meets this requirement?

A. Use Amazon Macie pattern matching as part of the ETLjob
B. Train and use the AWS Glue PySpark filter class in the ETLjob
C. Partition tables and use the ETL job to partition the data on patient name
D. Train and use the AWS Glue FindMatches ML transform in the ETLjob

Show Suggested Answer

Suggested Answer: D 🗳️

by rb39 at April 21, 2022, 12:01 p.m.

Disclaimers:

- ExamTopics website is not related to, affiliated with, endorsed or authorized by Amazon.
- Trademarks, certification & product names are used for reference only and belong to Amazon.

Comments

Submit Cancel

rb39

Highly Voted 3 years ago

Selected Answer: D

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. Reference: https://docs.aws.amazon.com/glue/latest/dg/machine-learning.html

upvoted 15 times

...

pk349

Most Recent 1 year, 11 months ago

D: I passed the test

upvoted 1 times

...

Hypnoss

2 years, 1 month ago

why not C?

upvoted 1 times

rsn

2 years, 1 month ago

partitioning based on name may not be a great idea. It will result in too many partitions

upvoted 3 times

...

rocky48

2 years, 9 months ago