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Exam AWS Certified Solutions Architect - Associate SAA-C03 All Questions

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Exam AWS Certified Solutions Architect - Associate SAA-C03 topic 1 question 812 discussion

Exam question from Amazon's AWS Certified Solutions Architect - Associate SAA-C03
Question #: 812
Topic #: 1
[All AWS Certified Solutions Architect - Associate SAA-C03 Questions]

A company hosts a data lake on Amazon S3. The data lake ingests data in Apache Parquet format from various data sources. The company uses multiple transformation steps to prepare the ingested data. The steps include filtering of anomalies, normalizing of data to standard date and time values, and generation of aggregates for analyses.

The company must store the transformed data in S3 buckets that data analysts access. The company needs a prebuilt solution for data transformation that does not require code. The solution must provide data lineage and data profiling. The company needs to share the data transformation steps with employees throughout the company.

Which solution will meet these requirements?

  • A. Configure an AWS Glue Studio visual canvas to transform the data. Share the transformation steps with employees by using AWS Glue jobs.
  • B. Configure Amazon EMR Serverless to transform the data. Share the transformation steps with employees by using EMR Serverless jobs.
  • C. Configure AWS Glue DataBrew to transform the data. Share the transformation steps with employees by using DataBrew recipes.
  • D. Create Amazon Athena tables for the data. Write Athena SQL queries to transform the data. Share the Athena SQL queries with employees.
Show Suggested Answer Hide Answer
Suggested Answer: C 🗳️
by asdfcdsxdfc at March 5, 2024, 10:58 p.m.
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LeonSauveterre
3 months ago
Selected Answer: C
A - AWS Glue doesn't focus on data profiling or provide an easy way for non-technical employees to collaborate on transformation steps. B - You need to code. C - AWS Glue DataBrew is a no-code tool specifically designed for data preparation and transformation. D - Let's say writing SQLs are not coding, still, Athena lacks data lineage, data profiling, and the ability to reuse transformations as recipes.
upvoted 2 times
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Lingo43
9 months ago
Selected Answer: C
AWS Glue DataBrew: This is a visual data preparation tool that allows you to clean and normalize data without writing code. It has built-in transformations for common tasks like filtering anomalies, normalizing dates, and generating aggregates. It also provides data lineage and profiling capabilities, which are required by the company. DataBrew Recipes: These are reusable workflows that define the data transformation steps. They can be easily shared with other employees, making it simple to collaborate on data preparation tasks.
upvoted 2 times
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Scheldon
9 months, 3 weeks ago
Selected Answer: C
AnswerC AWS Glue DataBrew is a visual data preparation tool that enables users to clean and normalize data without writing any code. Using DataBrew helps reduce the time it takes to prepare data for analytics and machine learning (ML) by up to 80 percent, compared to custom developed data preparation. You can choose from over 250 ready-made transformations to automate data preparation tasks, such as filtering anomalies, converting data to standard formats, and correcting invalid values. https://docs.aws.amazon.com/databrew/latest/dg/what-is.html
upvoted 4 times
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Linuslin
10 months, 2 weeks ago
Selected Answer: C
C is correct. https://docs.aws.amazon.com/databrew/latest/dg/recipes.html
upvoted 1 times
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seetpt
1 year ago
Selected Answer: C
Agree with C
upvoted 2 times
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asdfcdsxdfc
1 year ago
Selected Answer: C
Should be C
upvoted 4 times
...
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