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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 432 discussion

An ecommerce company wants to use machine learning (ML) algorithms to build and train models. The company will use the models to visualize complex scenarios and to detect trends in customer data. The architecture team wants to integrate its ML models with a reporting platform to analyze the augmented data and use the data directly in its business intelligence dashboards.

Which solution will meet these requirements with the LEAST operational overhead?

  • A. Use AWS Glue to create an ML transform to build and train models. Use Amazon OpenSearch Service to visualize the data.
  • B. Use Amazon SageMaker to build and train models. Use Amazon QuickSight to visualize the data.
  • C. Use a pre-built ML Amazon Machine Image (AMI) from the AWS Marketplace to build and train models. Use Amazon OpenSearch Service to visualize the data.
  • D. Use Amazon QuickSight to build and train models by using calculated fields. Use Amazon QuickSight to visualize the data.
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Suggested Answer: B 🗳️

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67db0ed
3 months, 3 weeks ago
https://docs.aws.amazon.com/quicksight/latest/user/sagemaker-integration.html
upvoted 1 times
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awsgeek75
10 months, 2 weeks ago
Selected Answer: B
Machine Learning = Sage Maker so B for least operational overhead A and D are not right technologies. C is possible but with more overhead of using AMI even if you can get OpenSearch to visualize the data somehow which I don't think is possible without massive overhead
upvoted 2 times
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Guru4Cloud
1 year, 2 months ago
Selected Answer: B
Use Amazon SageMaker to build and train models. Use Amazon QuickSight to visualize the data.
upvoted 2 times
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james2033
1 year, 4 months ago
Selected Answer: B
Question keyword "machine learning", answer keyword "Amazon SageMaker". Choose B. Use Amazon QuickSight for visualization. See "Gaining insights with machine learning (ML) in Amazon QuickSight" at https://docs.aws.amazon.com/quicksight/latest/user/making-data-driven-decisions-with-ml-in-quicksight.html
upvoted 2 times
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VellaDevil
1 year, 4 months ago
Selected Answer: B
Sagemaker.
upvoted 1 times
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TariqKipkemei
1 year, 5 months ago
Selected Answer: B
Business intelligence, visualiations = AmazonQuicksight ML = Amazon SageMaker
upvoted 2 times
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antropaws
1 year, 5 months ago
Selected Answer: B
Most likely B.
upvoted 1 times
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omoakin
1 year, 6 months ago
Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy ML models quickly.
upvoted 1 times
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cloudenthusiast
1 year, 6 months ago
Amazon SageMaker is a fully managed service that provides a complete set of tools and capabilities for building, training, and deploying ML models. It simplifies the end-to-end ML workflow and reduces operational overhead by handling infrastructure provisioning, model training, and deployment. To visualize the data and integrate it into business intelligence dashboards, Amazon QuickSight can be used. QuickSight is a cloud-native business intelligence service that allows users to easily create interactive visualizations, reports, and dashboards from various data sources, including the augmented data generated by the ML models.
upvoted 2 times
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Efren
1 year, 6 months ago
Selected Answer: B
ML== SageMaker
upvoted 1 times
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nosense
1 year, 6 months ago
Selected Answer: B
B sagemaker provide deploy ml models
upvoted 1 times
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