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Exam AWS Certified Data Engineer - Associate DEA-C01 topic 1 question 78 discussion

Exam question from Amazon's AWS Certified Data Engineer - Associate DEA-C01
Question #: 78
Topic #: 1
[All AWS Certified Data Engineer - Associate DEA-C01 Questions]

A company extracts approximately 1 TB of data every day from data sources such as SAP HANA, Microsoft SQL Server, MongoDB, Apache Kafka, and Amazon DynamoDB. Some of the data sources have undefined data schemas or data schemas that change.
A data engineer must implement a solution that can detect the schema for these data sources. The solution must extract, transform, and load the data to an Amazon S3 bucket. The company has a service level agreement (SLA) to load the data into the S3 bucket within 15 minutes of data creation.
Which solution will meet these requirements with the LEAST operational overhead?

  • A. Use Amazon EMR to detect the schema and to extract, transform, and load the data into the S3 bucket. Create a pipeline in Apache Spark.
  • B. Use AWS Glue to detect the schema and to extract, transform, and load the data into the S3 bucket. Create a pipeline in Apache Spark.
  • C. Create a PySpark program in AWS Lambda to extract, transform, and load the data into the S3 bucket.
  • D. Create a stored procedure in Amazon Redshift to detect the schema and to extract, transform, and load the data into a Redshift Spectrum table. Access the table from Amazon S3.
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Suggested Answer: B 🗳️
by rralucard_ at Feb. 2, 2024, 2:28 p.m.
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GiorgioGss
Highly Voted 7 months, 1 week ago
Selected Answer: B
Least effort = B
upvoted 6 times
...
rralucard_
Highly Voted 8 months, 4 weeks ago
Selected Answer: B
B. Use AWS Glue to detect the schema and to extract, transform, and load the data into the S3 bucket. Create a pipeline in Apache Spark.
upvoted 5 times
...
Christina666
Most Recent 6 months, 2 weeks ago
Selected Answer: B
Glue ETL
upvoted 1 times
...
kj07
7 months, 2 weeks ago
The option with the least operational overhead is B.
upvoted 3 times
...
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