AWS Certified Data Engineer Associate DEA-C01 Practice Question
A health-tech startup ingests one-second sensor readings from thousands of wearables through Amazon Kinesis Data Streams. They must retrieve the most recent metrics for an individual patient in under 10 ms for real-time dashboards, and allow data scientists to run overnight ad-hoc SQL scans across months of historical data. Which data storage configuration offers the lowest cost and operational overhead while meeting both access patterns?
Write readings to an Amazon ElastiCache for Redis cluster for dashboard queries and periodically export Redis snapshots to Amazon S3 for Athena analytics.
Store the readings in an Amazon DynamoDB table keyed by patient_id and timestamp, use DynamoDB Streams to write Parquet files to Amazon S3, and query the S3 data with Amazon Athena.
Load all readings into an Amazon Redshift RA3 cluster by using COPY from Kinesis and build materialized views that dashboards query directly.
Ingest every reading into an Amazon RDS for PostgreSQL instance with provisioned IOPS and add Aurora read replicas for analytics queries.
DynamoDB is purpose-built for key-value access with single-digit millisecond latency, so using patient_id as the partition key lets the application fetch the latest record for one patient well under the 10 ms target. Enabling a sort key on timestamp keeps recent items together and allows simple queries such as "ORDER BY timestamp DESC LIMIT 1". DynamoDB Streams can capture every insert and invoke an AWS Lambda function or Kinesis Data Firehose to batch the changes into Amazon S3. Converting the batches to columnar Parquet files keeps storage inexpensive and gives good scan performance. Amazon Athena is serverless and can directly run SQL across the S3 data without provisioning or managing infrastructure, satisfying the overnight analytics requirement at very low cost. The other options either cannot meet the latency goal (Amazon Redshift, Amazon RDS), or require continuously running an in-memory cache plus manual snapshot exports (ElastiCache for Redis), which increases both cost and operational complexity.
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AWS Certified Data Engineer Associate DEA-C01
Data Store Management
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