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Exam AWS Certified Data Engineer - Associate DEA-C01 topic 1 question 17 discussion

Exam question from Amazon's AWS Certified Data Engineer - Associate DEA-C01
Question #: 17
Topic #: 1
[All AWS Certified Data Engineer - Associate DEA-C01 Questions]

A data engineer is building a data pipeline on AWS by using AWS Glue extract, transform, and load (ETL) jobs. The data engineer needs to process data from Amazon RDS and MongoDB, perform transformations, and load the transformed data into Amazon Redshift for analytics. The data updates must occur every hour.
Which combination of tasks will meet these requirements with the LEAST operational overhead? (Choose two.)

  • A. Configure AWS Glue triggers to run the ETL jobs every hour.
  • B. Use AWS Glue DataBrew to clean and prepare the data for analytics.
  • C. Use AWS Lambda functions to schedule and run the ETL jobs every hour.
  • D. Use AWS Glue connections to establish connectivity between the data sources and Amazon Redshift.
  • E. Use the Redshift Data API to load transformed data into Amazon Redshift.
Show Suggested Answer Hide Answer
Suggested Answer: BC 🗳️
by milofficial at Jan. 20, 2024, 11:59 a.m.
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DevoteamAnalytix
2 weeks ago
Selected Answer: AD
I was not sure about A - But in AWS console => Glue => Triggers => Add Trigger I have found the Trigger type: "Schedule - Fire the trigger on a timer."
upvoted 1 times
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lucas_rfsb
1 month, 2 weeks ago
Selected Answer: CD
I found this question actually confusing. In which step the transformation would be implemented itself? I can be wrong, but with Glue triggers we would only run the job, but not the transformation logic itself. In this way, I would go in C and D
upvoted 1 times
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milofficial
2 months ago
Selected Answer: AD
Not a clear question - B would kinda make sense - but AD seems to be more correct
upvoted 2 times
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GiorgioGss
2 months, 1 week ago
Selected Answer: AD
A - this is obvious and D -https://docs.aws.amazon.com/glue/latest/dg/console-connections.html
upvoted 3 times
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TonyStark0122
3 months, 2 weeks ago
A. Configure AWS Glue triggers to run the ETL jobs every hour. D. Use AWS Glue connections to establish connectivity between the data sources and Amazon Redshift. Explanation: Option A: Configuring AWS Glue triggers allows the ETL jobs to be scheduled and run automatically every hour without the need for manual intervention. This reduces operational overhead by automating the data processing pipeline. Option D: Using AWS Glue connections simplifies connectivity between the data sources (Amazon RDS and MongoDB) and Amazon Redshift. Glue connections abstract away the details of connection configuration, making it easier to manage and maintain the data pipeline.
upvoted 2 times
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rralucard_
3 months, 3 weeks ago
Selected Answer: AD
AWS Glue triggers provide a simple and integrated way to schedule ETL jobs. By configuring these triggers to run hourly, the data engineer can ensure that the data processing and updates occur as required without the need for external scheduling tools or custom scripts. This approach is directly integrated with AWS Glue, reducing the complexity and operational overhead. AWS Glue supports connections to various data sources, including Amazon RDS and MongoDB. By using AWS Glue connections, the data engineer can easily configure and manage the connectivity between these data sources and Amazon Redshift. This method leverages AWS Glue’s built-in capabilities for data source integration, thus minimizing operational complexity and ensuring a seamless data flow from the sources to the destination (Amazon Redshift).
upvoted 3 times
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milofficial
3 months, 4 weeks ago
Selected Answer: AB
Lambda triggers for Glue jobs make me dizzy
upvoted 2 times
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