DEA-C01 Data Operations and Support Practice Test 9 — 15 Questions

Question 1

A data engineer needs to automate the backup of an Amazon RDS for PostgreSQL database. Which AWS service can be used to schedule and manage the backups?

Accepted Answer

AWS Backup. AWS Backup is a fully managed backup service that can automate backups of RDS databases. Option A (Amazon S3) is incorrect because S3 is an object storage service, not a backup scheduling service. Option B (AWS Lambda) is incorrect because while Lambda can be used for custom automation, it is not the primary managed service for backup scheduling. Option D (Amazon CloudWatch) is incorrect because CloudWatch is for monitoring and observability, not backup management.

Answer

Amazon S3

Answer

AWS Lambda

Answer

Amazon CloudWatch

Question 2

Refer to the exhibit. A data engineer has attached this IAM policy to a user. The user reports being unable to upload files to my-bucket from an on-premises network with a public IP of 203.0.113.5. What is the issue?

Accepted Answer

The user's IP address is not within the allowed IP range. The IAM policy includes a condition that restricts access to requests originating from the IP range 10.0.0.0/16 (a private range). The user's on-premises network has a public IP of 203.0.113.5, which is not within that range, so the condition fails and the upload is denied. Option A is incorrect because the resource ARN does include the bucket itself (arn:aws:s3:::my-bucket/*), so that is not the issue. Option C is incorrect because the policy explicitly allows s3:PutObject. Option D is incorrect because there is no condition requiring server-side encryption.

Answer

The resource ARN does not include the bucket itself

Answer

The user does not have s3:PutObject permission

Answer

The bucket requires server-side encryption

Question 3

A data engineer is troubleshooting a slow-running Amazon Athena query. The query scans a large amount of data. Which TWO actions can improve query performance? (Choose TWO.)

Accepted Answer

Convert the data to Parquet or ORC format.. Converting data to columnar formats like Parquet or ORC reduces the amount of data scanned, and partitioning the table on frequently filtered columns allows Athena to skip reading irrelevant partitions. Both actions improve query performance. Option B (encryption) does not affect performance. Option C (increasing timeout) only allows more time for a slow query, not improving performance. Option E (SELECT *) scans all columns, which increases data scanned and worsens performance.

Answer

Enable encryption at rest.

Answer

Increase the Athena query timeout.

Answer

Use SELECT * to retrieve all columns.

Question 4

A company is experiencing high costs from Amazon Redshift. The data engineer wants to optimize costs. Which THREE actions should the engineer take? (Choose THREE.)

Accepted Answer

Right-size the cluster based on workload analysis.. Right-sizing the cluster based on workload analysis ensures that the provisioned resources (number and type of nodes) match the actual compute and storage demands. Over-provisioned clusters waste money on unused capacity, while under-provisioned clusters cause performance issues. Analyzing metrics like CPU utilization, disk usage, and query queue wait times helps identify the optimal node count and instance type, directly reducing costs.

Answer

Increase the frequency of automated snapshots.

Answer

Increase the number of nodes to improve performance.

Question 5

A data engineer notices that an AWS Glue ETL job processing data from Amazon S3 to Amazon Redshift has been failing intermittently with the error 'S3ServiceException: SlowDown'. Which action is MOST likely to resolve this issue?

Accepted Answer

Implement exponential backoff and retry logic in the Glue job.. The 'S3ServiceException: SlowDown' error indicates that the AWS Glue job is making requests to Amazon S3 at a rate that exceeds the bucket's request rate limits. Implementing exponential backoff and retry logic (option C) is the most effective solution because it reduces the effective request rate by introducing delays between retries, allowing S3 to recover from throttling. Option A is incorrect because increasing partitions would likely increase the number of concurrent requests, exacerbating throttling. Option B is incorrect because switching to a larger worker type does not affect the rate of S3 requests. Option D is incorrect because S3 Transfer Acceleration improves network transfer speed but does not reduce request throttling.

Answer

Increase the number of partitions in the Glue job to parallelize reads.

Answer

Switch from a Standard to a G.2X large Glue worker type.

Answer

Enable S3 Transfer Acceleration on the source bucket.

Question 6

A data engineer needs to ensure that data in an Amazon S3 bucket is not publicly accessible. Which TWO measures should the engineer implement? (Choose TWO.)

Accepted Answer

Attach a bucket policy that denies access to 'Principal': '*' unless specific conditions are met.. To prevent public access to an S3 bucket, you can use bucket policies that explicitly deny access to anonymous principals (option A) or enable S3 Block Public Access settings (option C). Option B is incorrect because lifecycle policies manage object retention and deletion, not access control. Option D is incorrect because versioning protects against accidental deletion/overwrites but does not control access. Option E is incorrect because default encryption secures data at rest but does not restrict public access.

Answer

Create a lifecycle policy to delete objects after 30 days.

Answer

Enable S3 Versioning on the bucket.

Answer

Enable default encryption on the bucket.

Question 7

A company runs a data pipeline that ingests streaming data via Amazon Kinesis Data Streams, processes it with an AWS Lambda function, and stores results in Amazon DynamoDB. The Lambda function sometimes fails due to 'ProvisionedThroughputExceededException' on the DynamoDB table. Which combination of steps should a data engineer take to resolve this issue?

Accepted Answer

Enable DynamoDB auto scaling and configure a dead-letter queue for the Lambda function.. Enabling DynamoDB auto scaling allows the table to adjust its provisioned throughput based on actual traffic patterns, which helps prevent 'ProvisionedThroughputExceededException' when the Lambda function writes to DynamoDB. Additionally, configuring a dead-letter queue (DLQ) for the Lambda function ensures that records that fail due to throttling are captured and can be reprocessed later, preventing data loss. Option B is incorrect because increasing the Lambda function timeout does not address DynamoDB throughput limits. Option C is incorrect because increasing the number of Kinesis shards may increase the rate of Lambda invocations, potentially worsening the throttling issue. Option D is incorrect because increasing Lambda reserved concurrency could allow more concurrent invocations, which may exacerbate throughput exceedance, and disabling retries would cause data loss.

Answer

Increase the Lambda function timeout and enable batch windows.

Answer

Increase the number of Kinesis shards to reduce Lambda invocations.

Answer

Increase Lambda reserved concurrency and disable retries.

Question 8

A data engineer needs to troubleshoot a failed AWS Glue job that reads from an Amazon RDS for MySQL database. The error log shows 'Communications link failure'. Which step should the engineer take FIRST?

Accepted Answer

Check that the security group associated with the Glue job allows outbound traffic to the RDS database.. A 'Communications link failure' often indicates network connectivity issues; verifying that the Glue job's security group allows outbound traffic to the RDS database is the first troubleshooting step. Option A is wrong because the error is not about authentication. Option C is wrong because the issue is not about table structure. Option D is wrong because the error is not about permissions.

Answer

Increase the job timeout and retry count.

Answer

Verify that the database username and password are correct in the Glue connection.

Answer

Confirm that the table schema in MySQL matches the Glue Data Catalog.

Question 9

A company uses AWS DMS to migrate a 2 TB Oracle database to Amazon RDS for PostgreSQL. The migration completes successfully, but data validation shows some tables have missing rows. The task is configured for ongoing replication using change data capture (CDC). What is the MOST likely cause of the missing rows?

Accepted Answer

Source tables missing primary keys. If a table lacks a primary key, DMS cannot uniquely identify rows for CDC, leading to missed changes. Option A is wrong because the endpoint connection is valid (migration completed). Option B is wrong because CDC captures changes from redo logs, not the source database directly. Option D is wrong because DMS supports large objects with proper configuration.

Answer

Source database archive log retention period too short

Answer

Large objects (LOBs) not supported by the target

Answer

Insufficient storage on the DMS replication instance

Question 10

A company uses Amazon EMR to process large datasets stored in Amazon S3. The data engineer notices that EMR tasks are failing with 'DiskOutOfSpace' errors. The cluster uses m5.xlarge instances with 1 EBS volume of 64 GB. What is the MOST cost-effective solution to resolve this issue?

Accepted Answer

Increase the EBS storage volume size for each instance and use spot instances for task nodes.. Increasing the EBS volume size provides additional disk space per instance, directly resolving the disk out-of-space error. Using spot instances for task nodes reduces cost. Option A is incorrect because mixing on-demand and spot instances does not increase per-instance disk space. Option C is incorrect because switching to D2 instances is more expensive and may not be necessary. Option D is incorrect because adding more task instances distributes the workload but does not increase the disk space available to each instance, so individual tasks may still fail due to disk space.

Answer

Use a mix of on-demand and spot instances for core nodes.

Answer

Switch to D2 instances which have more instance store volume.

Answer

Increase the number of task instances to distribute the workload.

Question 11

A data engineer is optimizing an Amazon Redshift cluster that runs a nightly ETL workload. The engineer notices that the query performance degrades over the week and improves after a VACUUM operation. Which action should the engineer take to automate this maintenance and minimize impact on performance?

Accepted Answer

Schedule a VACUUM command using a query scheduler like Amazon EventBridge.. It enables automated scheduling of VACUUM using Amazon EventBridge or Redshift's query scheduler, ensuring regular maintenance without manual intervention. Option A is wrong because manual intervention only when performance degrades is not automated and allows performance to degrade unnecessarily. Option B is wrong because disabling auto vacuum and running manual VACUUM nightly is not as efficient or integrated as using a scheduler, and it may disrupt the ETL if not timed properly. Option D is wrong because dropping and recreating tables weekly is disruptive and loses data or requires complex re-creation logic, whereas VACUUM re-sorts data in place.

Answer

Run VACUUM manually only when performance degrades significantly.

Answer

Disable auto vacuum and run a manual VACUUM every night after the ETL.

Answer

Drop and recreate the tables weekly to avoid unsorted data.

Question 12

A team uses Amazon Kinesis Data Analytics to process streaming data. They notice that the application's output is delayed. Which AWS service can be used to monitor the application's performance and identify bottlenecks?

Accepted Answer

Amazon CloudWatch. (Amazon CloudWatch) is correct because CloudWatch provides metrics and logs for monitoring Kinesis Data Analytics application performance, such as CPU utilization, memory usage, and throughput, helping to identify bottlenecks causing output delays. Option A (AWS CloudTrail) is used for auditing API calls, not performance monitoring. Option C (Amazon Athena) is an interactive query service for analyzing data in S3, not for monitoring real-time streaming applications. Option D (AWS X-Ray) traces requests through applications but is not the primary tool for monitoring Kinesis Data Analytics performance.

Answer

AWS CloudTrail

Answer

Amazon Athena

Answer

AWS X-Ray

Question 13

A data engineer is troubleshooting an AWS Glue job that reads from an Apache Kafka topic using a Glue connector. The job fails with 'TimeoutException'. The Kafka cluster is in a VPC. Which step should the engineer take FIRST?

Accepted Answer

Check the security group and network ACLs associated with the Glue job's VPC.. A 'TimeoutException' when reading from Kafka in a VPC typically indicates a network connectivity issue. The first step should be to verify that the security group and network ACLs allow traffic between the Glue job's VPC and the Kafka cluster. Option B (increasing consumer timeout) may be considered after confirming network connectivity, but it is not the first step. Option C (updating the connector) is unrelated to network timeouts. Option D (changing job type) does not address the root cause.

Answer

Increase the Kafka consumer session timeout.

Answer

Update the Glue connector to the latest version.

Answer

Change the Glue job type from Spark to Python Shell.

Question 14

A company runs a daily batch process that reads data from Amazon S3, transforms it with AWS Glue, and loads it into Amazon Redshift. The process takes 6 hours, but the business requires completion within 4 hours. Which design change would MOST reduce runtime?

Accepted Answer

Load data directly from S3 to Redshift using COPY command, then transform in Redshift. Loading data directly from S3 to Redshift using the COPY command eliminates the AWS Glue transformation step, which is the primary bottleneck. The COPY command is optimized for high-speed bulk loads, and performing transformations within Redshift (e.g., using SQL or stored procedures) can often be faster than an external ETL tool. Option A (increasing Glue workers) may help parallelism but does not address the overhead of the Glue job itself. Option C (S3 Select) reduces the data volume scanned by Glue but still requires the Glue transformation. Option D (columnar storage) is already the default in Redshift and does not reduce the Glue job runtime.

Answer

Increase the number of Glue workers

Answer

Use S3 Select to filter data before Glue

Answer

Switch to columnar storage in Redshift

Question 15

A company uses Amazon S3 to store raw data files. An AWS Glue crawler creates metadata in the Data Catalog. The data engineer discovers that the crawler is not detecting new partitions after new data is added to the S3 bucket. What is the MOST likely cause?

Accepted Answer

The IAM role used by the crawler does not have kms:Decrypt permission for the KMS key that encrypts the new partitions.. When new partitions are added to an S3 bucket encrypted with AWS KMS (SSE-KMS), the AWS Glue crawler needs the kms:Decrypt permission to read the object metadata and detect the new partitions. Without this permission, the crawler cannot list the objects or determine the partition structure, so it fails to update the Data Catalog. Option B is incorrect because the crawler's partition detection is not disabled by default; the 'Crawl all folders' setting is for crawling subfolders, not for partition detection. Option C is incorrect because AWS Glue crawlers can handle large numbers of objects, and there is no specific limit that would prevent partition detection. Option D is incorrect because S3 event notifications are not required for crawling; the crawler periodically scans the S3 location and does not rely on events to detect changes.

Answer

The crawler configuration has 'Crawl all folders' disabled.

Answer

The S3 bucket has too many objects, exceeding the crawler's limit.

Answer

The crawler does not have S3 event notifications enabled.