1.0 Data Ingestion and Transformation DEA-C01 Practice Quiz
170 exam-style questions covering 34% of the DEA-C01 exam. Instant feedback on every answer, progress tracking, no signup required.
This domain is part of the AWS Certified Data Engineer Associate practice test. Each question is tagged by exam objective and difficulty so you can drill exactly the areas you need.
Sample Questions
A data engineering team must ingest clickstream events continuously from thousands of clients and allow multiple consumers to process the stream independently. Which AWS service should be used for the streaming source?
- A. Amazon Kinesis Data Streams
- B. Amazon S3
- C. Amazon EventBridge
- D. AWS Transfer Family
Amazon Kinesis Data Streams stores ordered records in shards and lets multiple consumers read the clickstream with controllable retention and replay for downstream processing. This is the correct answer.
A streaming pipeline must deliver events into Apache Flink processing with low latency and later archive raw data to S3. Which ingestion source is most appropriate?
- A. Kinesis Data Streams feeding stream processing and archival consumers
- B. AWS Glue crawlers
- C. Amazon Managed Service for Apache Flink
- D. AWS IAM
Kinesis Data Streams can act as the durable streaming source for low-latency consumers while also supporting additional consumers that archive records to S3. This is the correct answer.
A company already runs Apache Kafka producers on premises and wants an AWS-managed Kafka-compatible ingestion layer. Which service should the data engineer select?
- A. AWS Glue Data Quality
- B. Amazon Managed Streaming for Apache Kafka (Amazon MSK)
- C. Amazon Kinesis Data Streams
- D. AWS Systems Manager
Amazon MSK provides managed Kafka brokers, so existing Kafka producers and consumers can continue using Kafka protocols while AWS operates the cluster infrastructure. This is the correct answer.
A nightly data load reads several terabytes of CSV files from Amazon S3 into an ETL job. Which source pattern is being used?
- A. AWS PrivateLink
- B. Amazon S3 batch ingestion
- C. AWS Lake Formation
- D. Amazon ECS
Amazon S3 batch ingestion fits scheduled processing of files that have already landed in object storage rather than continuous event-by-event processing. This is the correct answer.
A company needs to ingest database tables in bulk from an Oracle source before enabling ongoing replication. Which AWS service is suitable?
- A. Amazon Q
- B. AWS DMS full load
- C. Apache Iceberg
- D. AWS Transfer Family
AWS DMS full load copies existing source tables into AWS targets and is appropriate before enabling ongoing change replication. This is the correct answer.
A DynamoDB-backed application needs downstream processing whenever table items are inserted or updated. Which source should be read?
- A. Amazon MSK
- B. S3 Versioning
- C. DynamoDB Streams
- D. Apache Iceberg
DynamoDB Streams captures item-level changes from the table in time order, which gives the pipeline a native change stream for inserts and updates. This is the correct answer.
A partner SaaS application must periodically export customer records into an AWS data lake with minimal custom code. Which service should be considered?
- A. Amazon Managed Service for Apache Flink
- B. Amazon Bedrock
- C. Amazon AppFlow
- D. AWS IAM
Amazon AppFlow provides managed integrations from SaaS applications to AWS destinations, reducing custom extraction code for scheduled batch transfers. This is the correct answer.
A migration pipeline must continuously replicate changes from an on-premises relational database into AWS for analytics. Which source capability fits?
- A. AWS Glue workflows
- B. Amazon CloudWatch Logs
- C. AWS Lambda
- D. AWS DMS change data capture
AWS DMS change data capture reads ongoing database changes after initial load, supporting continuous ingestion from the source database into AWS targets. This is the correct answer.
Key Terms in This Domain
- AWS Lambda: Serverless compute for event-driven data processing
- AWS SAM: Framework to package and deploy serverless data pipelines
- AWS Glue: Serverless ETL service for data preparation and integration
- Amazon Kinesis Data Streams: Real-time streaming ingestion at scale
- Replayability: Ability of an ingestion pipeline to reprocess historical events without data loss
- Amazon Athena: Serverless SQL query engine for data in S3 and federated sources
- Amazon EMR: Managed Hadoop/Spark/Presto/Hive/Flink for big data processing
- AWS Glue DataBrew: Visual data preparation tool with no-code transformations
- Amazon Managed Service for Apache Flink: Real-time stream processing with Apache Flink
- Amazon MSK: Fully managed Apache Kafka for high-throughput streaming
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