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Exam AWS Certified Database - Specialty topic 1 question 327 discussion

Exam question from Amazon's AWS Certified Database - Specialty
Question #: 327
Topic #: 1
[All AWS Certified Database - Specialty Questions]

A legal research company wants to build a recommendation engine on AWS that connects datasets to help lawyers create legal arguments. The recommendation engine will collect millions of unstructured text documents from third-party sources to identify connections between documents without users needing to manually compare the documents.

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

  • A. Build a graph-based recommendation engine by using Amazon Neptune. Search the documents for vertices with relationships among the different sources to connect.
  • B. Create an AWS Lambda application in which the documents are uploaded into Amazon S3. Populate Amazon DynamoDB tables with the metadata of the documents for users to search.
  • C. Develop a serverless document scanner by using Amazon Textract to analyze the text from the various sources. Store the detected text in an Amazon Aurora database for analysis.
  • D. Define the data sources in an Amazon S3 data lake. Analyze the documents by using AWS Glue. Query the documents for relationships by using Amazon Athena.
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Suggested Answer: A 🗳️
by TQM__9MD at July 14, 2023, 1:32 a.m.
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MultiAZ
1 year, 6 months ago
Selected Answer: A
This can be implemented using an RDF graph in Neptune
upvoted 2 times
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zyjp
1 year, 9 months ago
this is the last question 327 ? not 335 ?
upvoted 2 times
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Pranava_GCP
1 year, 10 months ago
Selected Answer: A
A. Amazon Neptune. https://docs.aws.amazon.com/neptune/latest/userguide/intro.html
upvoted 2 times
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chen0305_099
1 year, 10 months ago
Selected Answer: A
AAAAAA
upvoted 2 times
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marcelodba
1 year, 10 months ago
Selected Answer: A
GraphDB
upvoted 2 times
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EueChan
1 year, 10 months ago
Selected Answer: A
Its A. Graph database for relationships. also Amazon Athena doesn't work with unstructured documents !
upvoted 3 times
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Windy
1 year, 12 months ago
It's A.
upvoted 3 times
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TQM__9MD
1 year, 12 months ago
Selected Answer: D
Option D, defining data sources in an Amazon S3 data lake, analyzing the documents using AWS Glue, and querying the relationships between documents using Amazon Athena, is the recommended solution. It allows for the storage and analysis of unstructured text documents in the data lake, while leveraging AWS Glue and Amazon Athena for efficient querying of document relationships. This approach minimizes operational overhead while meeting the stated requirements.
upvoted 2 times
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