DEA-C01 Practice Test 28 — 15 Questions

Question 1

A data engineer needs to ingest on-premises CSV files into Amazon S3 every hour. The files are less than 1 GB each. Which service is the most cost-effective and requires the least operational overhead?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

AWS DataSync. AWS DataSync is the most cost-effective and least overhead option for scheduled, recurring transfers of on-premises CSV files to S3. It provides a simple agent-based setup, supports hourly scheduling, and handles files under 1GB efficiently without complex configuration. In contrast, Amazon Kinesis Data Firehose is designed for streaming data ingestion, not batch file transfers; AWS Snowball Edge is intended for large-scale offline data migrations, not hourly incremental transfers; and AWS Database Migration Service (DMS) is specialized for migrating databases, not file transfers.

Answer

Amazon Kinesis Data Firehose

Answer

AWS Snowball Edge

Answer

AWS Database Migration Service (DMS)

Question 2

A company ingests JSON data from an S3 bucket into a Glue ETL job. The data contains nested structures and arrays. The team wants to flatten the data into a tabular format for analysis in Athena. Which Glue transformation is appropriate?

Accepted Answer

Relationalize. The Relationalize transformation is specifically designed to flatten nested JSON and arrays into a tabular format suitable for Athena. Option A (Map) applies a function to each record but does not flatten structures. Option C (Filter) selects rows based on a condition. Option D (DropNullFields) removes null fields but does not address nested structures.

Answer

Map

Answer

Filter

Answer

DropNullFields

Question 3

A data pipeline uses AWS Glue to process large CSV files. The team notices that some jobs fail with out-of-memory errors. Which TWO configuration changes can help mitigate this issue?

Accepted Answer

Increase the number of DPUs for the Glue job.. Options B and C are correct: increasing the number of DPUs provides more memory, and enabling autoscaling allows the job to automatically scale resources as needed. Option A (reducing DPUs) would worsen the problem by limiting resources. Option D (converting to Parquet) can improve performance but is not a direct configuration change for the Glue job itself. Option E (job bookmarks) is for incremental processing and does not affect memory.

Answer

Reduce the number of DPUs to limit concurrency.

Answer

Convert input files from CSV to Parquet.

Answer

Enable job bookmarks.

Question 4

A company needs to ingest data from an on-premises Oracle database into Amazon S3 for analytics. The data volume is about 1 TB initially, with daily incremental updates of about 10 GB. Which TWO services can be combined to achieve this with minimal custom code?

Accepted Answer

Amazon S3. The correct combination is AWS DMS (Database Migration Service) for migration and Amazon S3 as the target. DMS can perform full load and ongoing replication with minimal custom code, making it suitable for the initial 1 TB load and daily 10 GB increments. AWS Glue (option A) could be used but often requires more custom code for change data capture (CDC) compared to DMS. Amazon Kinesis Data Streams (option B) is designed for real-time streaming data, not database migration. Amazon Athena (option C) is a query service, not a data movement service. Therefore, the correct answers are D (Amazon S3) and E (AWS DMS).

Answer

AWS Glue

Answer

Amazon Kinesis Data Streams

Answer

Amazon Athena

Question 5

A company uses AWS Glue to transform data in S3. The Glue job fails with memory errors. Which THREE actions can help resolve this?

Accepted Answer

Optimize the transformation to use pushdown predicates.. Options A, B, and C are correct. Using pushdown predicates (A) reduces the amount of data read by filtering at the data source, which can alleviate memory pressure. Using a larger worker type (B), such as G.2X, increases the memory available per worker, directly addressing out-of-memory errors. Increasing the number of DPUs (C) adds more workers, distributing the memory load. Option D (increasing job timeout) does not solve memory issues, and Option E (decreasing DPUs) would reduce available memory, making the problem worse.

Answer

Increase the job timeout.

Answer

Decrease the number of DPUs.

Question 6

A data engineer attached this IAM policy to a Lambda function used to transform data in S3. The function is unable to write output to the bucket. What is the most likely reason?

Accepted Answer

The policy does not allow the s3:ListBucket action on the bucket.. The policy allows GetObject and PutObject on objects, but not the s3:ListBucket action required to check existence or list objects. The function likely needs ListBucket to write or verify.

Answer

The resource ARN is missing the bucket-level ARN.

Answer

The policy does not allow the s3:DeleteObject action.

Answer

The policy does not allow the s3:PutObjectAcl action.

Question 7

A company needs to ingest streaming data from an existing Amazon Kinesis Data Streams into Amazon S3 with partitioning by date. Which TWO services can accomplish this with minimal coding? (Choose two.)

Accepted Answer

Amazon Kinesis Data Firehose

Answer

AWS Glue Streaming

Answer

Amazon Kinesis Data Analytics

Answer

Amazon S3 Transfer Acceleration

Question 8

A data engineer is designing a data ingestion pipeline for real-time clickstream data. Which TWO services can be used to ingest the data into Amazon Kinesis Data Streams?

Accepted Answer

Kinesis Producer Library (KPL). Options B and D are correct. The Kinesis Producer Library (KPL) is a library for producers to send data to Kinesis Data Streams. AWS SDK can also be used directly. Option A is wrong because Amazon S3 is a storage service, not a producer. Option C is wrong because Kinesis Data Firehose is a downstream consumer or delivery service, not a producer. Option E is wrong because AWS Glue is an ETL service, not a producer.

Answer

Amazon S3

Answer

Kinesis Data Firehose

Answer

AWS Glue

Question 9

A company uses AWS Lambda to process messages from an Amazon SQS queue. The messages contain JSON payloads that need to be transformed and written to an Amazon DynamoDB table. Recently, the Lambda function has been timing out and messages are being sent to the dead-letter queue (DLQ). What is the BEST way to troubleshoot and resolve this issue?

Accepted Answer

Increase the Lambda function timeout and monitor DynamoDB write capacity to ensure it is not throttling.. The Lambda function is timing out, which suggests the function's execution duration is exceeding its configured timeout. Increasing the timeout gives the function more time to process messages. Additionally, if DynamoDB write capacity is insufficient, throttling can cause retries that further delay processing, so monitoring and possibly increasing write capacity units addresses the root cause of timeouts.

Answer

Use a standard SQS queue instead of a DLQ to reprocess failed messages automatically.

Answer

Switch the SQS queue to a FIFO queue to ensure exactly-once processing.

Answer

Increase the visibility timeout of the SQS queue to 30 minutes.

Question 10

A company is ingesting data from multiple sources into Amazon S3 using AWS Glue. The data is then transformed using Apache Spark on Amazon EMR. The data engineer wants to reduce the cost of storing and processing data by compressing the ingested files. Which THREE file formats support compression and are commonly used with Spark? (Choose THREE.)

Accepted Answer

ORC. Correct options: A, B, and E. ORC, Parquet, and Avro all support compression and are commonly used with Spark. These formats are columnar (ORC and Parquet) or row-based with efficient compression (Avro), making them suitable for analytics. JSON and CSV support compression but are not columnar and less efficient for Spark processing; they are not the best choices for reducing storage and processing costs in this context.

Answer

JSON

Answer

CSV

Question 11

A company uses Amazon Kinesis Data Firehose to deliver data to an Amazon S3 bucket. The data delivery is delayed by up to 5 minutes. The engineer wants to reduce the delay to under 1 minute. Which parameter should be adjusted?

Accepted Answer

Decrease the buffer interval in Kinesis Data Firehose.. Decreasing the buffer interval reduces the time Kinesis Data Firehose waits before delivering a batch, thus lowering latency to under 1 minute. Option A is incorrect because error logging to CloudWatch does not affect delivery timing. Option B is incorrect because increasing the buffer size would actually increase the delay as Firehose waits for more data to accumulate. Option C is incorrect because enabling data compression reduces storage size but has no impact on delivery frequency.

Answer

Enable error logging to CloudWatch.

Answer

Increase the buffer size in Kinesis Data Firehose.

Answer

Enable data compression.

Question 12

A company needs to ingest data from an external FTP server into AWS S3. The FTP server is not accessible from the internet. Which AWS service should be used to securely transfer the data?

Accepted Answer

AWS Transfer Family with SFTP endpoint in a VPC. AWS Transfer Family supports SFTP and can be configured with a VPC endpoint to securely transfer data from an FTP server in a private network to S3. Option A is wrong because Kinesis Data Firehose is designed for streaming data ingestion, not for FTP transfers. Option C is wrong because AWS DataSync requires network connectivity to the source, and the FTP server is not internet-accessible. Option D is wrong because AWS Snowball Edge is intended for large-scale offline data transfers, not regular FTP-based transfers.

Answer

Kinesis Data Firehose

Answer

AWS DataSync

Answer

AWS Snowball Edge

Question 13

A data engineer is using AWS Glue ETL to transform data from an S3 data lake. The job fails with a memory error. Which approach should be used to resolve this issue without major code changes?

Accepted Answer

Increase the number of DPUs allocated to the Glue job. Increasing the number of DPUs (Data Processing Units) allocated to the Glue job provides more memory and parallelism. Option A is wrong because rewriting in PySpark is a major code change. Option B is wrong because using a smaller file format may not address memory issues. Option D is wrong because using a different service is unnecessary.

Answer

Rewrite the ETL script in PySpark instead of Scala

Answer

Change the input file format from CSV to Parquet

Answer

Use Amazon EMR instead of AWS Glue

Question 14

A data engineer is designing a data ingestion pipeline for IoT sensor data. The data arrives as JSON via AWS IoT Core, and must be stored in Amazon S3 in partitioned Parquet format. The pipeline must handle late-arriving data (up to 1 hour) and ensure exactly-once processing. Which combination of services should the engineer use?

Accepted Answer

Amazon Kinesis Data Firehose with data transformation via AWS Lambda, delivering to Amazon S3.. Amazon Kinesis Data Firehose is the correct choice because it can directly ingest streaming data from AWS IoT Core, use a built-in AWS Lambda function to transform JSON to Parquet, and deliver the data to Amazon S3 with automatic partitioning. It also supports buffering and retry logic to handle late-arriving data (up to 1 hour) and provides exactly-once delivery to S3 when configured with the appropriate error handling and idempotent transformations.

Answer

Amazon Kinesis Data Streams with AWS Lambda for transformation and Amazon S3.

Answer

Amazon Simple Queue Service (SQS) with AWS Lambda for transformation and Amazon S3.

Answer

AWS Glue streaming jobs consuming from Amazon Kinesis Data Streams and writing to Amazon S3.

Question 15

A data engineer needs to ingest data from an on-premises Oracle database into Amazon S3 for analytics. The data changes frequently and the engineer wants to capture both initial load and incremental changes with minimal latency. Which TWO AWS services should be used together? (Choose TWO.)

Accepted Answer

AWS Database Migration Service (DMS). AWS DMS (Option A) is correct because it can perform an initial load of data from an on-premises Oracle database to Amazon S3 and then continuously replicate incremental changes using change data capture (CDC) with minimal latency. Amazon Kinesis Data Streams (Option E) complements DMS by enabling near-real-time streaming of data changes, which can be further processed or stored in S3. Option B (Lambda) is not a direct replacement for database replication; it can process events but does not natively capture database changes. Option C (Glue) is an ETL service, not designed for real-time replication. Option D (Transfer Family) is for file transfers, not database replication.

Answer

AWS Lambda

Answer

AWS Glue

Answer

AWS Transfer Family