DEA-C01 Mock Exam 74 — 25 Questions

Question 1

A data engineer is designing a data ingestion pipeline that uses Amazon Kinesis Data Firehose to deliver data to Amazon S3. The engineer wants to ensure that the data is organized in a directory structure by year, month, day, and hour. Which TWO configurations should the engineer set on the Firehose delivery stream? (Choose TWO.)

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

Accepted Answer

Enable dynamic partitioning. Correct options: A and B. Option A is correct because enabling dynamic partitioning allows Firehose to use partition keys from the data, such as timestamps, to automatically create folder structures in S3. Option B is correct because setting a custom prefix with the expression '!{timestamp:yyyy}/!{timestamp:MM}/!{timestamp:dd}/!{timestamp:HH}/' defines the directory hierarchy by year, month, day, and hour. Option C is incorrect because using a Lambda function to write to S3 with a desired prefix is not necessary; Firehose handles the prefix natively. Option D is incorrect because format conversion to Parquet is unrelated to directory organization. Option E is incorrect because S3 bucket versioning does not affect directory structure.

Answer

Use an AWS Lambda function to write to S3 with the desired prefix

Answer

Enable format conversion to Parquet

Answer

Configure an S3 bucket with versioning enabled

Question 2

A data engineer is setting up a data pipeline using AWS Glue. The engineer wants to monitor job failures and receive notifications. Which TWO services can be used together for this purpose?

Accepted Answer

Amazon CloudWatch. Amazon CloudWatch (B) is correct because it is the native monitoring service for AWS Glue, capturing job metrics, logs, and state changes. You can configure CloudWatch alarms to trigger on job failures, which then invoke Amazon SNS (C) to send notifications via email, SMS, or other endpoints. Together, they provide a complete monitoring and alerting solution without additional orchestration.

Answer

AWS Step Functions

Answer

Amazon Kinesis Data Streams

Answer

Amazon SQS

Question 3

A company uses Amazon DynamoDB with provisioned capacity. During a sales event, write traffic spikes and some requests receive ProvisionedThroughputExceeded exceptions. The reads are within limits. The data engineer needs to minimize latency for the spike without manual intervention. Which solution is MOST cost-effective?

Accepted Answer

Enable DynamoDB auto scaling for write capacity with a target utilization of 70%.. DynamoDB auto scaling for write capacity automatically adjusts the provisioned write capacity units (WCUs) based on the actual traffic pattern, using a target utilization of 70% to balance cost and performance. This eliminates manual intervention and handles spikes efficiently by scaling up before throttling occurs, while remaining cost-effective since capacity scales down when traffic subsides.

Answer

Use Amazon SQS to buffer write requests and process them in batches.

Answer

Disable auto scaling and set write capacity to the peak observed value.

Answer

Enable DynamoDB Accelerator (DAX) to cache write operations.

Question 4

A logistics company ingests GPS tracking data from thousands of vehicles into Amazon S3 via AWS Direct Connect. Each vehicle sends a message every 5 seconds, resulting in about 200,000 messages per second. Each message is about 200 bytes. The company uses AWS Glue to transform the data into a parquet format and load it into Amazon Redshift for real-time analytics. However, the Glue jobs are failing due to memory issues and the data is not being loaded into Redshift quickly enough. The company needs to reduce the latency of data availability in Redshift. Which action should the data engineer take?

Accepted Answer

Use Amazon Kinesis Data Firehose to ingest the data directly into S3 and then use Redshift Spectrum to query the data without loading.. Amazon Kinesis Data Firehose can ingest high-throughput streaming data (200,000 messages/sec) and deliver it to S3 in near-real-time (typically under 60 seconds). By using Redshift Spectrum to query the data directly in S3, the company avoids the latency and memory issues associated with AWS Glue batch transformations and Redshift bulk loads. This approach reduces data availability latency significantly.

Option A is incorrect because Amazon Kinesis Data Analytics adds processing overhead and does not directly solve the Glue memory issue or reduce latency to Redshift; it is more suitable for real-time streaming analytics, not for minimizing data ingestion latency.

Option B is incorrect because increasing the Redshift cluster size improves query performance and load speed but does not address the root cause: the Glue jobs are failing due to memory issues, and the data is not being transformed quickly enough. The bottleneck is upstream of Redshift.

Option D is incorrect because increasing DPUs and memory for the Glue job might resolve memory issues but does not significantly reduce latency; Glue batch processing still incurs minutes of delay, whereas Firehose provides near-real-time delivery.

Answer

Use Amazon Kinesis Data Analytics to process the data in real-time and write to Redshift directly.

Answer

Increase the size of the Redshift cluster to improve load performance.

Answer

Increase the number of DPUs and allocate more memory to the Glue job.

Question 5

A data engineer is setting up a data pipeline using Amazon Kinesis Data Firehose to deliver data to Amazon S3. The data must be transformed using an AWS Lambda function before delivery. Which THREE steps are required to configure this?

Accepted Answer

Create an AWS Lambda function that transforms the data.. Options B, C, and E are correct. To configure Kinesis Data Firehose with Lambda transformation, you need to create a Lambda function that transforms the data (B), attach an IAM role to the Firehose delivery stream that allows Firehose to invoke the Lambda function (C), and configure the Firehose delivery stream to use the Lambda function as a data transformation source (E). Option A is wrong because Lambda@Edge is used with CloudFront, not Firehose. Option D is wrong because S3 event notifications are not used for Firehose transformation; they are used for other purposes like triggering Lambda on new S3 objects.

Answer

Create a Lambda@Edge function in the same Region.

Answer

Configure an S3 event notification to trigger the Lambda function when new data arrives.

Question 6

A data engineer is designing a streaming pipeline that ingests IoT sensor data from 10,000 devices. Each device sends a 1 KB message every second. The data must be processed in near real-time and stored in S3 for analytics. Which combination of services provides the most cost-effective solution?

Accepted Answer

Amazon Kinesis Data Streams with Kinesis Data Firehose delivery to S3.. B is correct because Kinesis Data Streams ingests high-throughput IoT data (10,000 messages/sec at 1 KB each) with low latency, and Kinesis Data Firehose automatically batches and compresses data before delivering it to S3, eliminating the need for custom code or manual scaling. This combination provides the most cost-effective near-real-time solution by leveraging Firehose's built-in buffering and compression to minimize S3 storage costs and reduce the number of PUT requests.

Answer

AWS Data Pipeline with periodic S3 copy.

Answer

Amazon MSK (Managed Streaming for Kafka) with Kafka Connect S3 sink.

Answer

Amazon SQS FIFO queue with Lambda consumers writing to S3.

Question 7

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. B is correct because transferring 50 TB over a 100 Mbps connection would take approximately 48 days (50 TB * 1024 GB/TB * 8 bits/byte / (100 Mbps * 86400 seconds/day)), far exceeding the 2-week deadline. AWS Snowball Edge is a physical appliance that can be loaded with data on-premises and shipped to AWS, bypassing the slow network entirely and completing the transfer within days.

Answer

AWS DataSync

Answer

Amazon Kinesis Data Firehose

Answer

AWS Glue ETL job with JDBC connection to Hadoop

Question 8

A data engineer creates an Amazon DynamoDB table using the CloudFormation snippet in the exhibit. The application writes 200 items per second to the table. The engineer notices that many write requests are being throttled. What is the MOST likely reason?

Accepted Answer

The provisioned write capacity is too low for the application's write rate.. The table is provisioned with only 5 write capacity units, which allows 5 writes per second (each write up to 1 KB). With 200 writes per second, the table is severely under-provisioned. Option A is incorrect because the key schema is fine for a primary key. Option B is incorrect because the attribute type is correct. Option C is incorrect because the table name is valid.

Answer

The table does not have a sort key, causing hot partitions.

Answer

The attribute type for OrderID should be numeric for better performance.

Answer

The table name 'Orders' conflicts with an existing table.

Question 9

A company stores critical financial data in Amazon DynamoDB. To meet compliance requirements, the data must be encrypted at rest with a customer-managed key. Which solution should the data engineer implement?

Accepted Answer

Configure the DynamoDB table to use a customer managed key from AWS KMS.. AWS DynamoDB integrates with AWS KMS to support encryption at rest using customer-managed keys (CMKs). By selecting a customer-managed key from KMS during table creation or via an update, the company can meet compliance requirements for controlling the encryption key lifecycle, including rotation and access policies. This approach ensures that the data is encrypted using AES-256 encryption, with the key material managed by the customer rather than AWS.

Answer

Use AWS CloudHSM to generate a key and import it into DynamoDB.

Answer

Enable default encryption on the DynamoDB table using S3-managed keys.

Answer

Use AWS Certificate Manager to issue a certificate and configure TLS.

Question 10

A company is using Amazon DynamoDB with on-demand capacity for a gaming application. During a new game launch, write traffic spikes to 50,000 writes per second, but the application experiences throttling. The DynamoDB table has a partition key of 'game_id' and a sort key of 'timestamp'. What is the MOST likely cause of throttling?

Accepted Answer

Hot partitions due to a skewed access pattern on the partition key 'game_id'.. DynamoDB on-demand capacity automatically scales to handle traffic spikes, but it still has per-partition throughput limits. With 'game_id' as the partition key, a single popular game can create a hot partition where all writes target the same partition, exceeding the partition's maximum write capacity (1,000 write capacity units per partition) and causing throttling, even though the overall table capacity is sufficient.

Answer

The table has not enabled auto-scaling for writes.

Answer

The table's on-demand capacity is insufficient for the write spike.

Answer

The sort key is not optimal for write-heavy workloads.

Question 11

A team is designing a data ingestion pipeline to load JSON files from an Amazon S3 bucket into Amazon Redshift. The files arrive every 5 minutes, and each file is between 10 MB and 50 MB. The team wants to minimize the time between file arrival and data availability in Redshift. Which approach should the team use?

Accepted Answer

Use S3 Event Notifications to trigger an AWS Lambda function that runs the COPY command to load data into Redshift.. S3 Event Notifications can trigger an AWS Lambda function that executes the COPY command, loading data into Redshift with minimal latency. This approach avoids the overhead of scheduling or batching, directly responding to each file arrival to meet the 5-minute frequency and file size requirements.

Answer

Schedule an AWS Glue job to run every 5 minutes to load the data.

Answer

Use Amazon Redshift Spectrum to query the data directly from S3 without loading.

Answer

Configure Amazon Kinesis Data Firehose to stream data from S3 to Redshift.

Question 12

A company uses Amazon RDS for MySQL with Multi-AZ deployment. During a recent failover, the application experienced a brief outage because it cached the old database endpoint. Which solution would minimize application disruption during future failovers?

Accepted Answer

Use the RDS cluster endpoint in the application configuration.. The RDS cluster endpoint (also known as the writer endpoint) automatically points to the primary instance in a Multi-AZ deployment. During a failover, DNS is updated to resolve the cluster endpoint to the new primary instance, so the application does not need to cache or change the endpoint. This minimizes disruption by ensuring the application always connects to the current primary without manual intervention.

Answer

Use Amazon ElastiCache to cache database queries and absorb the failover delay.

Answer

Create a read replica in another Availability Zone and promote it during failover.

Answer

Configure the application to connect using the RDS instance's private IP address.

Question 13

A data engineer needs to store semi-structured JSON logs from multiple microservices in a cost-effective manner for ad-hoc querying using SQL. Which AWS service should be used?

Accepted Answer

Amazon Athena with data in S3. Amazon Athena is the correct choice because it allows you to query semi-structured JSON logs stored in S3 directly using standard SQL, without needing to load or transform the data. Athena's schema-on-read approach and pay-per-query pricing make it highly cost-effective for ad-hoc analysis of large volumes of log data, as you only pay for the data scanned during queries.

Answer

Amazon DynamoDB

Answer

Amazon RDS for MySQL

Answer

Amazon Kinesis Data Analytics

Question 14

A company has a data lake in Amazon S3 with millions of objects. The security team wants to enforce that all objects are encrypted with a specific customer-managed KMS key. The data engineer configures an S3 bucket policy to deny PutObject if the encryption is not set to that key. However, some existing objects are not encrypted with that key. What is the most efficient way to remediate the existing objects?

Accepted Answer

Use S3 Batch Operations to copy objects in the same bucket with the new encryption settings.. S3 Batch Operations can copy objects within the same bucket with new encryption settings, efficiently updating millions of objects in place. Option A is incorrect because S3 Cross-Region Replication replicates objects to a different bucket or region, not to the same bucket with changed encryption. Option B is inefficient compared to Batch Operations for large-scale remediation. Option D is incorrect because S3 Object Lambda transforms data on read, not at rest, so it does not change the stored encryption of existing objects.

Answer

Use S3 Cross-Region Replication to replicate objects to a new bucket with the correct encryption.

Answer

Write a script using the AWS SDK to iterate over all objects and re-upload them with the correct encryption.

Answer

Use S3 Object Lambda to dynamically encrypt objects on read.

Question 15

A company uses Amazon EMR to run Spark jobs on a transient cluster. The jobs process data from S3 and write results back to S3. The team wants to reduce costs by optimizing the cluster. Which action should the team take?

Accepted Answer

Use Spot Instances for the task nodes.. Using Spot Instances for task nodes in a transient EMR cluster significantly reduces compute costs because Spot Instances are spare AWS EC2 capacity offered at up to 90% discount compared to On-Demand. Since transient clusters are terminated after job completion, the risk of Spot Instance interruptions is mitigated—the job can simply be retried on a new cluster if needed. This directly addresses the cost optimization goal without sacrificing job functionality.

Answer

Increase the number of core nodes and use larger instance types.

Answer

Enable EMRFS consistent view.

Answer

Terminate the cluster after each job and manually restart it for the next job.

Question 16

Which TWO statements are true about Amazon S3 bucket policies and ACLs?

Accepted Answer

ACLs are a legacy access control mechanism that is still supported.. ACLs (Access Control Lists) are indeed a legacy access control mechanism that Amazon S3 continues to support for backward compatibility. While bucket policies and IAM policies are the modern, recommended approach, ACLs can still be used to grant basic read/write permissions to AWS accounts or predefined groups like AllUsers or AuthenticatedUsers.

Answer

When both exist, bucket policies are evaluated before ACLs.

Answer

ACLs can grant permissions to all authenticated AWS users.

Answer

ACLs support conditions such as IP address restrictions.

Question 17

A data engineer needs to securely store database credentials for an RDS instance. Which TWO AWS services can be used?

Accepted Answer

AWS Secrets Manager. AWS Secrets Manager is a dedicated service for managing secrets, including automatic rotation. AWS Systems Manager Parameter Store can also securely store secrets like database credentials as secure string parameters. AWS KMS is used for encryption key management, not for storing secrets. AWS IAM is for identity and access management. AWS CloudFormation is for infrastructure as code and does not natively store secrets.

Answer

AWS KMS

Answer

AWS IAM

Answer

AWS CloudFormation

Question 18

A company is using Amazon S3 as a data lake. The data engineer needs to ensure that all objects uploaded to a specific bucket are automatically replicated to a bucket in another AWS Region for disaster recovery. Which configuration should the engineer implement?

Accepted Answer

Enable S3 Cross-Region Replication (CRR) on the source bucket.. S3 Cross-Region Replication (CRR) is the correct choice because it automatically replicates objects from a source bucket in one AWS Region to a destination bucket in a different AWS Region, meeting the disaster recovery requirement for geographic separation. CRR requires versioning to be enabled on both buckets and replicates new objects asynchronously after upload.

Answer

Enable S3 Same-Region Replication (SRR) on the source bucket.

Answer

Use S3 Transfer Acceleration to copy objects to the destination.

Answer

Use S3 Batch Operations to copy existing objects.

Question 19

A data engineer is troubleshooting a data pipeline that uses Amazon Kinesis Data Firehose to deliver data to Amazon S3. The engineer notices that the S3 bucket contains many small files (less than 1 MB). This is causing performance issues in downstream processing. What is the BEST way to reduce the number of small files?

Accepted Answer

Increase the buffer size to at least 128 MB in the Firehose delivery stream configuration.. Increasing the buffer size (e.g., to 128 MB) causes Firehose to deliver fewer, larger files, reducing the number of small files. Option B is incorrect because using a Lambda transformation does not inherently change buffering behavior. Option C is incorrect because changing the compression format (e.g., from GZIP to Snappy) affects storage size but not the number of files delivered. Option D is incorrect because decreasing the buffer interval would cause more frequent deliveries, creating more small files.

Answer

Use an AWS Lambda function to transform the data before delivery.

Answer

Change the compression format from GZIP to Snappy.

Answer

Decrease the buffer interval in the Firehose delivery stream configuration.

Question 20

A data engineer is configuring an Amazon Redshift cluster for compliance. The cluster must encrypt data at rest and automatically rotate the encryption key every year. Which steps should the engineer take? (Choose THREE.)

Accepted Answer

Create the Redshift cluster with encryption enabled.. The correct steps to meet the compliance requirements are A, B, and E. Option A is correct because encryption must be enabled during Redshift cluster creation; it cannot be added afterward. Option B is correct because using a customer-managed KMS key allows you to enable automatic yearly rotation of the key itself, satisfying the key rotation requirement. Option E is correct because specifying a customer-managed KMS key gives you control over the key and its rotation policy. Option C is incorrect because Redshift does not provide a native mechanism to rotate the cluster's encryption key; key rotation is handled at the KMS level. Option D is incorrect because encryption cannot be enabled on an existing unencrypted Redshift cluster; you must create a new cluster with encryption enabled.

Answer

Configure the Redshift cluster to rotate its encryption key every year.

Answer

Modify an existing unencrypted cluster to enable encryption.