AWS Certified Data Engineer Associate DEA-C01 Practice Question
A company stores user transactions in an Amazon DynamoDB table. The data engineering team must capture every change and land it in Amazon S3 as compressed Parquet files within 5 minutes so downstream analytics can query the data. The pipeline must be fully serverless, require the least custom code, and automatically evolve the schema when new attributes are added. Which solution meets these requirements?
Enable Kinesis Data Streams for the DynamoDB table and configure an Amazon Data Firehose delivery stream with data format conversion to write Parquet files to S3.
Trigger an AWS Lambda function from DynamoDB Streams to batch records, convert them to Parquet, and upload the files to S3.
Use AWS Database Migration Service (AWS DMS) to replicate the table directly to S3 in Parquet format.
Enable DynamoDB on-demand export to S3 and schedule an AWS Glue ETL job to convert the exported JSON files to Parquet.
Enable Kinesis Data Streams for the DynamoDB table and create an Amazon Data Firehose delivery stream that uses the DynamoDB stream as its source, enables data format conversion to Parquet, and delivers the output to S3. The integration is completely serverless, Firehose manages buffering and file creation, converts JSON to Parquet, and its schema-evolution setting adds new columns automatically. The other options either provide only periodic snapshots, require custom code in Lambda, or rely on AWS DMS, which needs a managed replication instance and is therefore not fully serverless.
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What is the role of Kinesis Data Streams in the pipeline?
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How does Amazon Kinesis Data Firehose handle data transformation and schema evolution?
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Why is this solution more serverless and efficient than AWS DMS or Lambda?
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What is Amazon Kinesis Data Firehose, and why is it important in this solution?
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How does enabling Kinesis Data Streams on a DynamoDB table work?
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What is schema evolution and how does Kinesis Data Firehose handle it?
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AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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