SAA-C03 Question 320

Community Discussion

Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.

• Chose A1

  Publish data to Amazon Kinesis Data Streams. Use Kinesis Data Analytics to query the data. • Kinesis Data Streams is designed for real-time data ingestion and can handle high throughput (1 MB/s is well within its capabilities). • Data durability: Kinesis Data Streams stores data for up to 7 days (default is 24 hours), which helps prevent data loss during EC2 instance reboots. • Kinesis Data Analytics allows you to run SQL queries on streaming data in near real-time, which satisfies the data science team’s requirement. • Scalable: Kinesis is designed to automatically scale with data volume, making it highly suitable for fluctuating ingestion

• Chose A1

  Also A because "The company’s data science team wants to query ingested data in near-real time" and kinesis data analytics is doing that. With option B we query the tada once is in the data lake.

• Chose A1

  Option a for me. I will assume that the EC2 instance is responsible for placing the data into the correct database. Therefore, we just need to wait for the instance to reboot. Since we can store the data in Kinesis Data Streams for up to 7 days, we are covered in that regard. For option B, we are forced to use Amazon Redshift, and the problem statement does not mention anything related to that. I would choose option A because it does not affect the original requirements, and it helps us avoid in-flight data loss as requested.