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AWS Certified Data Engineer Associate DEA-C01 Practice Question

A company ingests application events as JSON records into an existing Amazon Kinesis Data Stream. The data engineering team must build an ongoing pipeline that delivers every new record into an Amazon Redshift cluster for analytics. The solution must require the least custom code and must automatically handle schema changes in the incoming JSON. Which approach meets these requirements?

  • Configure an AWS DMS task in full-load and change-data-capture mode with Kinesis Data Streams as the source endpoint and Amazon Redshift as the target endpoint.

  • Develop an AWS Glue streaming ETL job that reads from the Kinesis Data Stream and writes the data to Amazon Redshift using the JDBC writer.

  • Create a streaming ingestion materialized view in Amazon Redshift that reads directly from the Kinesis Data Stream and stores the data in a column of type SUPER.

  • Create an Amazon Kinesis Data Firehose delivery stream that transforms the JSON with AWS Lambda and loads the data into Amazon Redshift.

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