DEA-C01 Data Ingestion and Transformation Practice Test 25 — 15 Questions

Question 1

A data engineering team is designing a data ingestion pipeline that will receive millions of small JSON files per hour from external partners via API. The files should be stored in Amazon S3 and then transformed into Parquet for querying. Which approach is MOST cost-effective and scalable?

Accepted Answer

Use Amazon Kinesis Data Firehose to buffer and deliver data to S3, then use AWS Glue to convert to Parquet.. Option C is correct because Kinesis Firehose can ingest streaming data, buffer it, and deliver in batches to S3, and then a Glue job can convert to Parquet. Option A is wrong because Lambda has a payload limit and is not cost-effective for millions of files. Option B is wrong because Direct Connect is for dedicated network, not for API ingestion. Option D is wrong because EMR is overkill and more expensive.

Answer

Use AWS Lambda to process each file as it arrives and write to S3.

Answer

Use AWS Direct Connect to establish a dedicated network for file uploads.

Answer

Use Amazon EMR to process the files as they arrive in S3.

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

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 4

A company uses Amazon Kinesis Data Streams to ingest clickstream data from a website. The data must be transformed (e.g., enrich with user location) before being stored in Amazon S3. Which architecture is MOST efficient for this transformation?

Accepted Answer

Use Amazon Kinesis Data Analytics to transform the stream and output to Amazon Kinesis Data Firehose, which writes to S3.. Option B is correct because Kinesis Data Analytics can run SQL on the stream for enrichment, then output to Firehose for delivery to S3. Option A is wrong because Lambda can process each record but may be slower and more expensive for high throughput. Option C is wrong because Glue is batch, not streaming. Option D is wrong because EMR is more complex than needed.

Answer

Use AWS Glue to run a streaming ETL job.

Answer

Use Amazon EMR to consume the stream using Spark Streaming.

Answer

Use AWS Lambda to process each record from the stream and write to S3.

Question 5

A company has a 100 TB dataset stored on-premises in a Hadoop cluster. They want to ingest this data into Amazon S3 for processing with AWS Glue. The company has a limited time window and a slow internet connection. Which strategy is MOST appropriate?

Accepted Answer

Use AWS Snowball Edge to physically ship the data to AWS.. Option A is correct because AWS Snowball Edge is designed for large data transfers with limited network. Option B is wrong because Direct Connect may not be feasible if the connection is slow. Option C is wrong because DataSync is for smaller volumes and needs network. Option D is wrong because S3 Transfer Acceleration also requires a network connection.

Answer

Use AWS DataSync over the existing internet connection.

Answer

Use Amazon S3 Transfer Acceleration to speed up the upload.

Answer

Use AWS Direct Connect to establish a high-bandwidth connection.

Question 6

A data engineer needs to ingest streaming data from a social media API into Amazon S3 for batch analytics. The data arrives at a rate of 500 records per second. Which service should be used to capture the stream?

Accepted Answer

Amazon Kinesis Data Streams. Option B is correct because Kinesis Data Streams can capture high-throughput streaming data. Option A is wrong because SQS is for message queues, not for streaming analytics. Option C is wrong because SNS is for pub/sub notifications. Option D is wrong because MQ is for message brokers.

Answer

Amazon Simple Notification Service (SNS)

Answer

Amazon Simple Queue Service (SQS)

Answer

Amazon MQ

Question 7

A company is designing a data ingestion pipeline for real-time sensor data from thousands of devices. The data must be processed with low latency and stored in Amazon S3. Which TWO services would be appropriate for this use case? (Choose TWO.)

Accepted Answer

Amazon Kinesis Data Firehose. Option A is correct for ingestion, Option C is correct for delivery to S3. Option B is for batch ETL, not real-time. Option D is for ad-hoc querying. Option E is for batch data transfer.

Answer

AWS Glue

Answer

AWS DataSync

Answer

Amazon Athena

Question 8

A company uses AWS Glue to transform data from Amazon S3 into Parquet format. The job fails with an out-of-memory error for large files. Which TWO actions can resolve this issue? (Choose TWO.)

Accepted Answer

Increase the number of DPUs allocated to the job.. Option A increases memory, Option C increases parallelism. Option B is not relevant since the job reads from S3. Option D is for streaming. Option E is for debugging, not resolving OOM.

Answer

Change the input format from CSV to JSON.

Answer

Use the Glue streaming ETL feature.

Answer

Enable CloudWatch logs for detailed error analysis.

Question 9

A company is building a data lake on Amazon S3 and needs to ingest data from multiple sources. The ingestion must be automated and handle schema changes. Which THREE services can be used together to achieve this? (Choose THREE.)

Accepted Answer

AWS Glue Crawler. Option A, B, and D are correct: AWS Glue can crawl schemas, Kinesis Firehose can ingest streaming data, and Lambda can transform data. Option C is for data warehouse, not data lake. Option E is for big data processing, not ingestion automation.

Answer

Amazon Redshift

Answer

Amazon EMR

Question 10

An IAM policy is attached to an AWS Glue job. The job needs to read from and write to S3 buckets, and also trigger other Glue jobs. The job is failing with an AccessDenied error when trying to write to a bucket named 'example-bucket'. What is the MOST likely cause?

Accepted Answer

The bucket name in the resource ARN does not match the actual bucket name.. Option B is correct because the policy allows both GetObject and PutObject on the specified bucket, so the issue is likely that the bucket name is misspelled or the ARN is incorrect. Option A is wrong because the policy does allow Glue actions. Option C is wrong because the policy uses the correct ARN format. Option D is wrong because the policy does allow PutObject.

Answer

The policy does not include s3:PutObject action.

Answer

The policy uses a resource ARN with a wildcard, which is not allowed.

Answer

The policy does not allow Glue actions.

Question 11

A data engineer runs the describe-stream command and sees the output above. The stream has a retention period of 24 hours. The engineer needs to ensure that consumers can replay data for up to 7 days. Which action is required?

Accepted Answer

Use the IncreaseStreamRetentionPeriod API to set retention to 168 hours.. Option C is correct because to increase retention, you call IncreaseStreamRetentionPeriod. Option A is wrong because changing shard count does not affect retention. Option B is wrong because starting new consumers does not change retention. Option D is wrong because you can only increase retention up to 365 days.

Answer

Increase the number of shards to allow more data storage.

Answer

Delete the stream and recreate it with a longer retention period.

Answer

Create new consumer applications that read from the stream.

Question 12

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 13

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 14

A data engineering team is troubleshooting a slow AWS Glue ETL job that reads from an Amazon DynamoDB table and writes to Amazon S3 in Parquet format. The job processes 50 GB of data. Which action would most effectively improve job performance?

Accepted Answer

Increase the number of DPUs. Increasing the number of DPUs (Data Processing Units) allocated to the Glue job provides more parallelism and memory, which can significantly speed up processing. Using G.1X worker type with more memory can also help. Using S3 Select is for filtering within S3, not for DynamoDB. Changing to JSON format may reduce performance due to larger file size. Reducing batch size could slow down the job.

Answer

Use S3 Select to push down filters

Answer

Reduce the batch size in the DynamoDB connector

Answer

Change output to JSON format to reduce overhead

Question 15

A company needs to ingest data from an on-premises Oracle database into Amazon Redshift for analytics. The data volume is 500 GB and the network bandwidth is limited. Which AWS service should be used for the initial one-time data migration?

Accepted Answer

AWS Snowball. AWS Snowball is ideal for large data transfers over limited network bandwidth. It allows physical shipping of storage devices. AWS DMS can be used for ongoing replication, but for initial large volume with limited bandwidth, Snowball is more efficient. S3 Transfer Acceleration speeds up transfers, but still relies on network. Direct Connect improves network but may still be insufficient for 500 GB.

Answer

AWS Direct Connect

Answer

Amazon S3 Transfer Acceleration

Answer

AWS Database Migration Service (DMS)