DEA-C01 Practice Test 46 — 15 Questions

Question 1

A data engineer is designing a data ingestion pipeline for streaming data from IoT devices. The devices send JSON messages every second. The engineer needs to ingest the data with low latency and store it in Amazon S3 in Parquet format. Which TWO services should the engineer use together?

Accepted Answer

Amazon Kinesis Data Streams. Options B and D are correct. Kinesis Data Streams provides low-latency ingestion, and Kinesis Data Firehose can convert data to Parquet and deliver to S3. Option A (Glue) is batch-oriented. Option C (Athena) is for querying. Option E (Lambda) can be used but is not required for the conversion; Firehose can do it natively.

Answer

AWS Lambda

Answer

Amazon Athena

Answer

AWS Glue

Question 2

A company wants to import data from an external FTP server into Amazon S3 on a daily basis. The data volumes are moderate. Which AWS service is MOST suitable for this task?

Accepted Answer

AWS Transfer Family. Option D is correct because AWS Transfer Family provides fully managed support for SFTP, FTPS, and FTP, enabling direct transfer to S3. Option A is wrong because Glue cannot connect to FTP directly without a custom connector. Option B is wrong because DataSync is for moving data between on-premises and AWS, but it does not support FTP servers. Option C is wrong because S3 Transfer Acceleration is for speeding up uploads to S3 from clients, not for fetching from FTP.

Answer

Amazon S3 Transfer Acceleration

Answer

AWS DataSync

Answer

AWS Glue with a JDBC connection

Question 3

An IAM policy includes the above resource ARN for CloudWatch Logs. A data engineer needs to allow a Lambda function to create log streams and put logs to the log group 'my-log-group'. However, the Lambda function is failing with access denied. What is the issue?

Accepted Answer

The ARN does not include the log-stream portion.. Option B is correct because the ARN includes a wildcard for log streams, but the correct ARN for log streams should be 'arn:aws:logs:us-east-1:123456789012:log-group:my-log-group:log-stream:*'. However, the more common issue is that the ARN is missing the log-stream prefix. Option A is wrong because the ARN format is valid. Option C is wrong because the Lambda execution role needs permissions, not the function itself. Option D is wrong because the region is correct.

Answer

The region in the ARN does not match the Lambda function's region.

Answer

The Lambda function does not have an execution role.

Answer

The ARN is incorrectly formatted because of the wildcard.

Question 4

Which TWO AWS services can be used to ingest streaming data from a mobile application into Amazon S3 for near-real-time analytics? (Choose 2.)

Accepted Answer

Amazon Kinesis Data Firehose. Amazon Kinesis Data Firehose can directly ingest streaming data and deliver to S3. Amazon Kinesis Data Streams can also ingest data, but requires a consumer to write to S3. AWS Glue is for batch ETL. Amazon SQS is for message queuing. Amazon DynamoDB Streams captures changes in DynamoDB, not from mobile apps.

Answer

Amazon DynamoDB Streams

Answer

AWS Glue

Answer

Amazon SQS

Question 5

A data pipeline uses Amazon Kinesis Data Firehose to ingest log data from web servers and deliver it to Amazon S3. The data is then transformed by an AWS Glue job before being loaded into Amazon Redshift. The pipeline must handle a sudden spike in log volume without data loss. Which configuration change is MOST appropriate?

Accepted Answer

Configure Kinesis Data Firehose to back up all data to S3 in case of delivery failures.. Option C is correct because enabling S3 backup for failed records in Firehose ensures that if the delivery fails after retries, the data is stored in S3 and can be reprocessed later, preventing data loss. Option A is wrong because increasing S3 bucket size doesn't help with data loss. Option B is wrong because increasing Glue job timeout does not prevent data loss during ingestion. Option D is wrong because increasing Redshift concurrency does not affect the ingestion pipeline.

Answer

Increase the AWS Glue job timeout and allocate more DPUs.

Answer

Increase the number of nodes in the Redshift cluster to handle higher load.

Answer

Increase the S3 bucket size limit and enable versioning.

Question 6

Refer to the exhibit. A data engineer runs this AWS Glue Data Catalog DDL statement to create a table. The CSV files in 's3://my-bucket/sales/' use a pipe delimiter (|) instead of a comma. What change is needed to correctly read the data?

Accepted Answer

Change the 'field.delim' property to '|'.. Option A is correct. The SERDEPROPERTIES specify 'field.delim' = ',' but the files use pipe. Changing the delimiter to '|' will allow correct parsing. Option B is wrong because partition projection is not needed. Option C is wrong because the table already exists. Option D is wrong because the location is correct.

Answer

Change the LOCATION to read from a subfolder.

Answer

Add a partition projection configuration.

Answer

Run a crawler to detect the schema automatically.

Question 7

A company receives streaming clickstream data from its website. The data must be ingested with low latency and transformed in real time before being stored in Amazon S3. Which AWS service combination is most suitable for this use case?

Accepted Answer

Amazon Kinesis Data Streams with Amazon Kinesis Data Analytics. Option B is correct because Amazon Kinesis Data Streams ingests streaming data with low latency, and Kinesis Data Analytics can perform real-time transformations using SQL or Apache Flink. Option A is wrong because Kinesis Data Firehose is a delivery service that can transform data but with higher latency. Option C is wrong because AWS Glue is a batch ETL service. Option D is wrong because Amazon S3 is a storage service, not for real-time transformation.

Answer

Amazon S3 with S3 Object Lambda

Answer

Amazon Kinesis Data Firehose with AWS Lambda for transformation

Answer

AWS Glue jobs triggered by Amazon S3 events

Question 8

A data engineer is building a pipeline to ingest data from an on-premises Oracle database into Amazon S3. The pipeline must capture change data (CDC) in near real-time and handle schema changes. Which TWO AWS services should the engineer use?

Accepted Answer

AWS Glue Schema Registry. Options A and D are correct. AWS DMS with CDC captures ongoing changes, and AWS Glue Schema Registry handles schema evolution. Option B (Kinesis) is not for database CDC. Option C (Snowball) is batch. Option E (AppFlow) is for SaaS, not on-prem databases.

Answer

AWS Snowball Edge

Answer

Amazon AppFlow

Answer

Amazon Kinesis Data Streams with Kinesis Agent

Question 9

A data engineer is troubleshooting a slow AWS Glue ETL job that reads from Amazon S3 and writes to Amazon Redshift. The job processes 10 GB of CSV data. The engineer notices that the job runs with a single DPU and takes longer than expected. Which change would MOST likely improve performance?

Accepted Answer

Increase the number of DPUs and configure the job to use the S3 list implementation for parallel reads.. Option A is correct because increasing DPUs and using the S3 list implementation can parallelize reading. Option B is wrong because Parquet is more efficient, but the bottleneck may be parallelism. Option C is wrong because JDBC connections are for databases, not S3. Option D is wrong because Redshift Spectrum queries data in place, but the job is an ETL, not querying.

Answer

Replace Redshift with Amazon Redshift Spectrum.

Answer

Change the input format to Parquet and enable predicate pushdown.

Answer

Use a JDBC connection to read data directly from S3.

Question 10

A company wants to ingest streaming data from thousands of IoT devices into Amazon S3 with minimal latency and then transform the data using Spark SQL. Which AWS service should be used for data ingestion?

Accepted Answer

Amazon Kinesis Data Firehose. Amazon Kinesis Data Firehose is the best choice because it can ingest streaming data, buffer it, and deliver it to S3 with minimal latency. AWS Glue is for ETL jobs, not real-time ingestion. Amazon Athena is a query service. Amazon EMR can process data but is not optimized for ingestion.

Answer

Amazon EMR

Answer

AWS Glue

Answer

Amazon Athena

Question 11

Which THREE factors should be considered when selecting a data ingestion service for a high-volume, real-time streaming pipeline that requires exactly-once processing semantics? (Choose 3.)

Accepted Answer

Ability to replay records from a checkpoint. Exactly-once processing requires services that support idempotent writes and checkpoints. Kinesis Data Streams supports record replay and checkpointing. AWS Lambda can be used with Kinesis for idempotent processing. Amazon S3 provides idempotent PUT operations. Amazon DynamoDB can store checkpoints. Amazon Kinesis Data Firehose provides at-least-once delivery, not exactly-once. AWS Glue is batch-oriented.

Answer

Support for schema evolution

Answer

Ability to transform data in-flight

Question 12

A company wants to ingest streaming data from IoT devices into Amazon S3 using Amazon Kinesis Data Firehose. The data must be transformed from JSON to Parquet format before landing in S3. What is the SIMPLEST way to achieve this?

Accepted Answer

Use an AWS Lambda function as a data transformation in Kinesis Data Firehose to convert JSON to Parquet.. Option D is correct because Kinesis Data Firehose can use an AWS Lambda function for data transformation, and converting to Parquet can be done via a Lambda function. Option A is wrong because Firehose can deliver to S3 directly. Option B is wrong because Firehose can transform without a separate Glue job. Option C is wrong because Firehose does not natively support Parquet conversion without a transformation.

Answer

Configure Kinesis Data Firehose with a built-in Parquet converter.

Answer

Use Kinesis Data Firehose to deliver data directly to S3 in JSON format and run a nightly Glue job to convert to Parquet.

Answer

Use Kinesis Data Analytics to convert the data to Parquet before sending to Firehose.

Question 13

A company wants to ingest streaming data from thousands of IoT devices into AWS for real-time analytics. The data volume is variable and can spike unpredictably. The solution must be serverless and minimize operational overhead. Which AWS service should be used for ingestion?

Accepted Answer

Use Amazon Kinesis Data Streams to ingest and process data in real time.. Option B is correct because Amazon Kinesis Data Streams is a serverless streaming data service that can handle variable and high-throughput data from many sources, making it ideal for IoT data ingestion. Option A (Amazon SQS) is for message queuing, not real-time streaming analytics. Option C (Amazon Kinesis Data Firehose) is for loading streaming data into data stores, but it does not provide the same real-time processing capabilities as Kinesis Data Streams. Option D (AWS IoT Core) is a managed cloud service that lets connected devices easily and securely interact with cloud applications and other devices, but it is not primarily a streaming ingestion service for analytics.

Answer

Use Amazon Kinesis Data Firehose to load streaming data directly into Amazon S3.

Answer

Use Amazon SQS to queue messages and process them in batches.

Answer

Use AWS IoT Core to ingest data and route it to Amazon DynamoDB.

Question 14

A company is building a data lake on Amazon S3 and needs to ingest data from various on-premises sources. Which TWO AWS services can be used to transfer data securely over the internet?

Accepted Answer

AWS DataSync. Options A and C are correct because AWS DataSync can transfer data over the internet, and the AWS CLI can be used for uploads. Option B is incorrect because Direct Connect is a physical connection. Option D is incorrect because Snowcone is a physical device. Option E is incorrect because Kinesis Data Firehose is for streaming, not file transfer.

Answer

AWS Snowcone

Answer

Amazon Kinesis Data Firehose

Answer

AWS Direct Connect

Question 15

A company is building a data lake on Amazon S3 and needs to ingest data from multiple sources. Which of the following AWS services can be used to ingest and transform data in near real-time? (Select TWO.)

Accepted Answer

AWS Glue. Correct options: A and C. Kinesis Data Firehose can ingest streaming data and perform basic transformations. AWS Glue can be triggered by S3 events for near real-time transformation. Option B (Amazon Athena) is a query service, not ingestion. Option D (Amazon SQS) is a message queue. Option E (AWS Step Functions) is for orchestration.

Answer

Amazon Athena

Answer

AWS Step Functions

Answer

Amazon Simple Queue Service (SQS)