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Amazon MLS-C01 Exam - Topic 9 Question 10 Discussion

A Data Scientist needs to create a serverless ingestion and analytics solution for high-velocity, real-time streaming data.The ingestion process must buffer and convert incoming records from JSON to a query-optimized, columnar format without data loss. The output datastore must be highly available, and Analysts must be able to run SQL queries against the data and connect to existing business intelligence dashboards.Which solution should the Data Scientist build to satisfy the requirements?
A) Create a schema in the AWS Glue Data Catalog of the incoming data format. Use an Amazon Kinesis Data Firehose delivery stream to stream the data and transform the data to Apache Parquet or ORC format using the AWS Glue Data Catalog before delivering to Amazon S3. Have the Analysts query the data directly from Amazon S3 using Amazon Athena, and connect to Bl tools using the Athena Java Database Connectivity (JDBC) connector.
B) Write each JSON record to a staging location in Amazon S3. Use the S3 Put event to trigger an AWS Lambda function that transforms the data into Apache Parquet or ORC format and writes the data to a processed data location in Amazon S3. Have the Analysts query the data directly from Amazon S3 using Amazon Athena, and connect to Bl tools using the Athena Java Database Connectivity (JDBC) connector.
C) Write each JSON record to a staging location in Amazon S3. Use the S3 Put event to trigger an AWS Lambda function that transforms the data into Apache Parquet or ORC format and inserts it into an Amazon RDS PostgreSQL database. Have the Analysts query and run dashboards from the RDS database.
D) Use Amazon Kinesis Data Analytics to ingest the streaming data and perform real-time SQL queries to convert the records to Apache Parquet before delivering to Amazon S3. Have the Analysts query the data directly from Amazon S3 using Amazon Athena and connect to Bl tools using the Athena Java Database Connectivity (JDBC) connector.

Amazon MLS-C01 Exam - Topic 9 Question 10 Discussion

Actual exam question for Amazon's MLS-C01 exam
Question #: 10
Topic #: 9
[All MLS-C01 Questions]

A Data Scientist needs to create a serverless ingestion and analytics solution for high-velocity, real-time streaming data.

The ingestion process must buffer and convert incoming records from JSON to a query-optimized, columnar format without data loss. The output datastore must be highly available, and Analysts must be able to run SQL queries against the data and connect to existing business intelligence dashboards.

Which solution should the Data Scientist build to satisfy the requirements?

Show Suggested Answer Hide Answer
Suggested Answer: A

by Lashaunda at May 05, 2022, 04:37 PM

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Silva
8 months ago
C seems too complicated for this use case.
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Glory
8 months ago
D is the way to go for real-time analytics!
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Reena
8 months ago
Wait, can Lambda handle that much data without issues?
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Virgie
8 months ago
I think B is better for real-time processing.
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Mitsue
9 months ago
Option A sounds solid with Glue and Athena!
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Kara
9 months ago
I remember learning about vendor risk assessments in class, so I'm feeling confident I can get this right.
upvoted 0 times
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Aja
9 months ago
This question seems straightforward, I'm pretty confident I can answer it correctly.
upvoted 0 times
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Hayley
9 months ago
This seems like a tricky question. I'll need to think through the different options carefully.
upvoted 0 times
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