AWS Certified Data Engineer Associate DEA-C01 Practice Question

An e-commerce application writes clickstream events to an Amazon Kinesis Data Streams stream with 5 shards and an average ingest rate of 4 MB/s. A data engineering team must build a near-real-time ETL pipeline that enriches each record and delivers results to Amazon S3. Processing latency must stay below 1 second, and other existing consumers must remain unaffected. Which solution meets these requirements?

  • Create an Amazon Kinesis Data Firehose delivery stream with the existing Kinesis Data Streams stream as the source, enable data transformation with AWS Lambda, and deliver the data to Amazon S3.

  • Configure an AWS Glue streaming job that reads from the Kinesis Data Streams stream using Enhanced Fan-Out and writes enriched records to Amazon S3 in Apache Parquet format.

  • Enable Amazon DynamoDB Streams on a table, process the stream with an AWS Glue job, and store the enriched data in Amazon S3.

  • Develop a Java application on Amazon EC2 that continuously polls the stream with the GetRecords API, enriches each record, and uploads the output files to Amazon S3.

AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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