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Exam AWS Certified Machine Learning - Specialty topic 1 question 335 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty
Question #: 335
Topic #: 1
[All AWS Certified Machine Learning - Specialty Questions]

A bank has collected customer data for 10 years in CSV format. The bank stores the data in an on-premises server. A data science team wants to use Amazon SageMaker to build and train a machine learning (ML) model to predict churn probability. The team will use the historical data. The data scientists want to perform data transformations quickly and to generate data insights before the team builds a model for production.

Which solution will meet these requirements with the LEAST development effort?

  • A. Upload the data into the SageMaker Data Wrangler console directly. Perform data transformations and generate insights within Data Wrangler.
  • B. Upload the data into an Amazon S3 bucket. Allow SageMaker to access the data that is in the bucket. Import the data from the S3 bucket into SageMaker Data Wrangler. Perform data transformations and generate insights within Data Wrangler.
  • C. Upload the data into the SageMaker Data Wrangler console directly. Allow SageMaker and Amazon QuickSight to access the data that is in an Amazon S3 bucket. Perform data transformations in Data Wrangler and save the transformed data into a second S3 bucket. Use QuickSight to generate data insights.
  • D. Upload the data into an Amazon S3 bucket. Allow SageMaker to access the data that is in the bucket. Import the data from the bucket into SageMaker Data Wrangler. Perform data transformations in Data Wrangler. Save the data into a second S3 bucket. Use a SageMaker Studio notebook to generate data insights.
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Suggested Answer: B 🗳️
by GS_77 at Aug. 30, 2024, 7:34 p.m.
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MultiCloudIronMan
6 months ago
Selected Answer: B
Options A and C involve directly uploading data to SageMaker Data Wrangler, which might not be as scalable or efficient for large datasets. Option D adds an extra step of using SageMaker Studio notebooks, which increases the complexity and development effort.
upvoted 1 times
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Tkhan1
7 months, 1 week ago
Selected Answer: B
B is the correct option . A is not an option as 10 years data will be too much for local upload or on premise . So an intermediate storage is needed which is S3 .
upvoted 1 times
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aragon_saa
7 months, 3 weeks ago
Selected Answer: B
Answer is B
upvoted 1 times
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GS_77
7 months, 3 weeks ago
Selected Answer: B
option B is the most straightforward and efficient solution for the data science team to quickly perform data transformations and generate insights before building a model
upvoted 1 times
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