DEA-C01 Practice Test 30 — 15 Questions

Question 1

A company is using AWS Glue ETL to process data from Amazon RDS for MySQL to Amazon S3. The job runs daily and takes 2 hours to complete. The engineer wants to improve performance without increasing cost significantly. Which TWO actions should the engineer take? (Choose TWO.)

Accepted Answer

Add a partition column to the source table based on a date column.. Increasing the number of DPUs improves performance but increases cost; however, it's a common approach. Partitioning the source table helps parallel reads. Option A is correct. Option B is correct. Option C is wrong because reducing worker type would slow performance. Option D is wrong because DynamicFrame is recommended for Glue. Option E is wrong because AWS Glue does not support auto-scaling by default without additional configuration.

Answer

Switch to a smaller worker type (e.g., G.1X instead of G.2X).

Answer

Use Spark DataFrames instead of DynamicFrames.

Answer

Enable 'Auto Scaling' in the Glue job configuration.

Question 2

A data pipeline uses Amazon Kinesis Data Firehose to deliver data to an S3 bucket. The delivery stream is configured with a buffer interval of 60 seconds and a buffer size of 5 MB. The data arrives at an average rate of 2 MB per second. What is the expected time interval between S3 writes?

Accepted Answer

Approximately 2.5 seconds. Option A is correct because with 2 MB/s, the buffer size of 5 MB will be reached in 2.5 seconds, but the buffer interval is 60 seconds. Firehose writes when either condition is met first. Since the buffer size is reached much earlier, writes will occur approximately every 2.5 seconds. Option B, C, D are incorrect because they are based on the interval or miscalculations.

Answer

Approximately 30 seconds

Answer

Approximately 60 seconds

Answer

Approximately 10 seconds

Question 3

A company needs to transform JSON data from Amazon Kinesis Data Streams into Parquet format and store it in Amazon S3. The transformation includes simple field mappings and type conversions. Which approach is most cost-effective and serverless?

Accepted Answer

Use Amazon Kinesis Data Firehose with an AWS Lambda function for transformation and output to Parquet. Kinesis Data Firehose with built-in Lambda transformation can convert JSON to Parquet efficiently. Glue is heavier and more expensive for simple transforms; EC2 is not serverless; SageMaker is ML-focused.

Answer

Use Amazon EC2 instances running Apache Spark Streaming

Answer

Use Amazon SageMaker for transformation

Answer

Use an AWS Glue ETL job triggered by a Kinesis stream

Question 4

A company uses AWS DMS to migrate a 2 TB Oracle database to Amazon RDS for PostgreSQL. The migration is taking longer than expected. The task status shows 'Full load in progress' with a low 'Table throughput (rows/s)'. Which action would MOST improve throughput?

Accepted Answer

Increase the number of parallel tasks in the DMS task settings. Using multiple parallel tasks splits the load across threads, improving throughput. Increasing the DMS replication instance size also helps, but parallel tasks are more effective for large datasets.

Answer

Enable Multi-AZ on the DMS replication instance

Answer

Change the target table preparation mode to 'Do nothing'

Answer

Increase the number of shards in the source database

Question 5

A data engineer needs to transfer 50 TB of historical data from an on-premises Hadoop cluster to Amazon S3. The company has a slow internet connection (100 Mbps). The data must be transferred within 2 weeks. Which service should the engineer recommend?

Accepted Answer

AWS Snowball Edge. The correct answer is AWS Snowball Edge, a physical device for large data transfers over slow networks. 50 TB at 100 Mbps would take over 46 days, exceeding the 2-week deadline. Option A (AWS DataSync) uses the network and would be too slow. Option B (AWS Glue) is for ETL, not transfer. Option D (Amazon Kinesis) is for streaming.

Answer

AWS DataSync

Answer

Amazon Kinesis Data Firehose

Answer

AWS Glue ETL job with JDBC connection to Hadoop

Question 6

A data engineer needs to ingest data from an external HTTP API into Amazon S3. The API returns JSON data for a list of users, updated hourly. The engineer wants to use a serverless solution with minimal operational overhead. Which AWS service should the engineer use?

Accepted Answer

Amazon AppFlow with an HTTP connector on a scheduled flow.. Option D is correct because Amazon AppFlow can connect to HTTP APIs and load data to S3 on a schedule. Option A is wrong because Kinesis Data Firehose requires a stream source. Option B is wrong because Glue ETL can do it but requires more configuration. Option C is wrong because Lambda alone lacks scheduling.

Answer

Amazon Kinesis Data Firehose with a custom HTTP endpoint.

Answer

AWS Lambda function triggered by CloudWatch Events.

Answer

AWS Glue ETL job triggered by EventBridge.

Question 7

A company uses AWS DMS to migrate an on-premises PostgreSQL database to Amazon RDS for PostgreSQL. After initial load, ongoing replication is set up. The replication task shows 'Task status: failed with error: The specified LSN is not available in the source database logs.' What is the most likely cause?

Accepted Answer

The source database's WAL retention period is too short, and required logs have been purged.. The error indicates that the required WAL logs have been removed or are not accessible. Option A is correct because DMS needs WAL logs for CDC. Option B is wrong because network connectivity would cause a different error. Option C is wrong because DMS supports PostgreSQL. Option D is wrong because ongoing replication does not need a full load.

Answer

DMS does not support PostgreSQL as a source for ongoing replication.

Answer

The source database's network security group blocks outbound traffic to DMS.

Answer

The full load was incomplete, preventing CDC from starting.

Question 8

A data engineer is designing a streaming ingestion pipeline using Amazon Kinesis Data Streams with multiple consumers. The data must be processed by a Lambda function for real-time alerts and also stored in Amazon S3 for historical analysis. Which THREE components are needed to implement this architecture? (Choose THREE.)

Accepted Answer

Amazon Kinesis Data Firehose. Kinesis Data Streams is the ingestion layer. Lambda can be a consumer for real-time alerts. Kinesis Data Firehose can read from the stream and write to S3. Option A is correct. Option B is correct. Option D is correct. Option C is wrong because Kinesis Data Analytics is for running SQL or Flink, not needed here. Option E is wrong because SQS is for decoupling, not needed for this pattern.

Answer

Amazon Kinesis Data Analytics

Answer

Amazon SQS queue

Question 9

A company wants to ingest real-time data from a social media API into Amazon S3 for analysis. The API provides data as JSON records. Which AWS service is best suited for this ingestion?

Accepted Answer

Amazon Kinesis Data Firehose. Option D is correct because Amazon Kinesis Data Firehose can capture and load streaming data into S3 with minimal latency. Option A is wrong because AWS Glue is ETL, not real-time ingestion. Option B is wrong because Amazon SQS is a message queue, not designed for direct S3 loading. Option C is wrong because Amazon DataZone is for data cataloging, not ingestion.

Answer

AWS Glue

Answer

Amazon Simple Queue Service (SQS)

Answer

Amazon DataZone

Question 10

A data engineer needs to ingest data from an on-premises Apache Kafka cluster into Amazon S3. The data volume is about 10 TB per day. The engineer wants to set up a managed Kafka connector. Which AWS service should they use?

Accepted Answer

Amazon MSK Connect. Amazon MSK Connect is a fully managed Kafka Connect service that can run S3 sink connectors. Lambda is not a Kafka sink; Kinesis is a different streaming service; DMS is for databases.

Answer

AWS Database Migration Service

Answer

AWS Lambda with Kafka trigger

Answer

Amazon Kinesis Data Streams

Question 11

Refer to the exhibit. A Lambda function named 'IngestionProcessor' is failing. The engineer checks CloudWatch Logs and sees the log group exists but storedBytes is 0. Why might the logs show no data?

Accepted Answer

The Lambda execution role does not have permission to write logs to CloudWatch. The log group exists but has no log streams, meaning the function hasn't executed (or its execution role lacks logs:CreateLogStream and logs:PutLogEvents). The most common cause is missing IAM permissions for CloudWatch Logs.

Answer

The Lambda function is configured with a dead letter queue

Answer

The Lambda function has not been invoked yet

Answer

The log group is encrypted with a KMS key and the Lambda function lacks decrypt permission

Question 12

A data engineer needs to transform CSV files arriving in S3 into Parquet format and partition them by date. The transformation should be event-driven and run immediately after each file is uploaded. Which approach is most efficient?

Accepted Answer

Use S3 event notification to trigger an AWS Glue job. Option D (Use S3 event notification to trigger an AWS Glue job) is correct because Glue can be triggered by S3 events and supports Parquet conversion and partitioning. Option A (AWS Lambda) has a 15-minute timeout and may not handle large files. Option B (Amazon Athena CTAS) is not event-driven and does not automatically run on upload. Option C (Amazon EMR) is overkill for this use case.

Answer

Use an S3 event notification to invoke a Lambda function that converts the file

Answer

Use an Amazon EMR cluster running Spark to process files as they arrive

Answer

Use Amazon Athena CREATE TABLE AS SELECT (CTAS) on a schedule

Question 13

A company needs to ingest data from an external API that returns CSV files daily. The files range from 100 MB to 2 GB. The data should be landed in Amazon S3 and then transformed using AWS Glue. Which ingestion method is most cost-effective and requires the least operational overhead?

Accepted Answer

Schedule an AWS Lambda function to download the CSV file and upload it to Amazon S3. Option A is correct because AWS Lambda with a Python script can download the CSV files and upload to S3, and it is cost-effective for periodic small-to-medium files. Option B (Kinesis Data Firehose) is for streaming. Option C (DataSync) is for large-scale data transfers, not API pulling. Option D (Direct Connect) is a network connection, not an ingestion method.

Answer

Set up AWS DataSync to transfer the file from the API endpoint to S3

Answer

Use Amazon Kinesis Data Firehose with a direct PUT

Answer

Deploy an AWS Direct Connect connection to the external API for faster transfer

Question 14

A data engineer is ingesting streaming data from an IoT fleet into Amazon S3 using Amazon Kinesis Data Firehose. The data arrives as JSON, but the downstream analytics require Parquet format. Which Firehose transformation should the engineer configure?

Accepted Answer

Configure a Lambda function as a data transformation in Firehose to convert JSON to Parquet.. Option B is correct because Kinesis Data Firehose can convert JSON to Parquet using an AWS Lambda transformation. Option A is wrong because S3 lifecycle policies do not transform data format. Option C is wrong because Kinesis Data Analytics performs real-time analytics, not format conversion. Option D is wrong because S3 batch operations process existing objects, not streaming ingestion.

Answer

Use an S3 lifecycle policy to convert JSON to Parquet.

Answer

Use S3 Batch Operations to convert existing JSON objects to Parquet.

Answer

Use Kinesis Data Analytics to convert the stream to Parquet before writing to S3.

Question 15

A company is building a data lake on Amazon S3. The data sources include relational databases, streaming data, and log files. The data engineer needs to ensure that the data ingestion pipeline can handle schema evolution, support both batch and streaming, and provide a unified metadata catalog. Which THREE services should the engineer use? (Choose three.)

Accepted Answer

AWS Glue. Options A, C, and D are correct. AWS Glue provides a metadata catalog and ETL for batch. Kinesis Data Firehose handles streaming ingestion to S3. S3 stores the data. Option B is wrong because Athena is a query service, not ingestion. Option E is wrong because DynamoDB is not used for data lake ingestion.

Answer

Amazon DynamoDB

Answer

Amazon Athena