DEA-C01 Mock Exam 80 — 25 Questions

Question 1

A data engineer is designing a data ingestion pipeline for real-time clickstream data. The data must be available for both real-time analytics and batch processing. The engineer wants to use Amazon Kinesis Data Streams. Which THREE components should be included in the architecture?

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

Accepted Answer

Amazon Kinesis Data Streams. Amazon Kinesis Data Streams is the core ingestion service for real-time clickstream data, providing low-latency, durable storage of data records that can be consumed by multiple applications simultaneously. It enables both real-time analytics (via Kinesis Data Analytics or KCL applications) and batch processing (by integrating with Kinesis Data Firehose to deliver data to Amazon S3).

Answer

Amazon Kinesis Data Analytics

Answer

Amazon SQS as a buffer

Question 2

The exhibit shows the lifecycle configuration for an S3 bucket. Objects in the bucket are 200 days old on average. What will happen to the objects?

Accepted Answer

Objects are in GLACIER now and will be deleted after 365 days from creation.. The lifecycle configuration shows a current version action to transition to GLACIOR (a misspelling of GLACIER) immediately (0 days after creation) and an expiration action to permanently delete the object 365 days after creation. Since the objects are already 200 days old on average, they have already been transitioned to GLACIER storage class. The expiration rule will delete them 365 days from their creation date, not from the current time.

Answer

Objects will be transitioned to GLACIER after 90 days and deleted after 365 days.

Answer

Objects will be transitioned to GLACIER after 200 days and deleted after 365 days.

Answer

Objects will be deleted after 90 days.

Question 3

A company uses AWS DMS to migrate data from Oracle to Aurora MySQL. During the ongoing replication, the target table shows duplicate primary key errors. What is the most likely cause?

Accepted Answer

The target table has an auto-increment column, and DMS is inserting explicit values that conflict.. When DMS replicates into a target table with an auto-increment column, it attempts to insert explicit values from the source. If the target's auto-increment counter has already generated a value matching one of those explicit inserts, a duplicate primary key error occurs. This is the most likely cause because DMS does not automatically skip or re-map auto-increment columns unless explicitly configured.

Answer

DMS is using 'Limited LOB mode' and truncating LOB data, causing row mismatches.

Answer

The source table has a trigger that inserts additional rows.

Answer

The DMS task is configured with 'Parallel apply' threads that cause race conditions.

Question 4

A data engineer is designing a data ingestion pipeline for real-time clickstream data. The data must be available for both real-time analytics and batch processing. The engineer wants to use Amazon Kinesis Data Streams. Which THREE components should be included in the architecture?

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

Accepted Answer

AWS Glue. AWS IoT Core (D) securely ingests sensor data via MQTT and routes it to a Kinesis data stream using a rule. AWS Glue Streaming ETL (A) consumes from the stream, adds a timestamp, filters malformed records, and writes the cleaned data to Kinesis Data Firehose (E). Firehose buffers and delivers the data to Amazon S3 within minutes, meeting the near-real-time requirement.

Answer

Amazon Athena

Answer

Amazon Simple Queue Service (SQS)

Question 5

A company is using AWS Glue to run ETL jobs that process data from Amazon S3 and load it into Amazon Redshift. The data engineer notices that the Glue job is failing with the error 'S3ServiceException: Access Denied' when writing to the staging S3 bucket. Which TWO actions should the engineer take to resolve this issue?

Accepted Answer

Verify that the IAM role used by the Glue job has the s3:PutObject permission for the staging bucket.. Options B and E are correct. The Glue job's IAM role must have s3:PutObject permission on the staging S3 bucket (option B). Additionally, the S3 bucket policy must explicitly allow the Glue job's IAM role to perform s3:PutObject (option E). Option C is incorrect because AWS Glue uses the IAM role attached to the job for S3 operations, not the Glue service principal; granting the service principal write access is unnecessary and not a standard practice. Option A is incorrect because the error is a permission issue, not a script path issue. Option D is incorrect because the error is about writing to the staging bucket, not reading from the source bucket.

Answer

Ensure that the Glue job script is correctly referencing the S3 bucket path.

Answer

Ensure that the S3 bucket has a bucket policy that allows the AWS Glue service principal to write objects.

Answer

Verify that the IAM role has s3:GetObject permission for the source bucket.

Question 6

A data engineer is designing a data lake on Amazon S3. The data is ingested from multiple sources and needs to be partitioned by year, month, day, and event type for efficient querying with Amazon Athena. Which S3 key prefix structure is most appropriate?

Accepted Answer

s3://bucket/event_type=events/year=2024/month=01/day=01/data.parquet. Uses Hive-style partitioning (event_type=events/year=2024/month=01/day=01), which Athena and other query engines natively support. This structure allows Athena to perform partition pruning, reading only the relevant directories based on WHERE clause filters, significantly reducing data scanned and improving query performance. Option D also uses Hive-style partitioning but with a different order of partition keys (day, month, year). While still valid, this non-standard order may cause issues with automatic partition discovery when using MSCK REPAIR TABLE, which expects the partition order to match the table definition. Therefore, option C is the most appropriate because it follows the common convention of listing partitions from coarse to fine granularity (year > month > day) and can be easily loaded into Athena without additional configuration.

Answer

s3://bucket/events/2024-01-01/event_type=data.parquet

Answer

s3://bucket/2024/01/01/event_type/events/data.parquet

Answer

s3://bucket/day=01/month=01/year=2024/event_type=events/data.parquet

Question 7

A data engineer needs to audit data access events in Amazon S3. Which AWS service should be used to record and monitor API calls for S3 buckets?

Accepted Answer

AWS CloudTrail. (AWS CloudTrail) is correct because it records API calls for S3 buckets, enabling auditing and monitoring of data access events. Option B (AWS Config) is incorrect as it tracks resource configuration changes, not API calls. Option C (Amazon Macie) is incorrect because it discovers sensitive data using machine learning. Option D (Amazon GuardDuty) is incorrect as it is a threat detection service.

Answer

AWS Config

Answer

Amazon Macie

Answer

Amazon GuardDuty

Question 8

A data engineer sees this AWS Glue table definition in the Data Catalog. The engineer wants to query this table with Amazon Athena, but the query returns zero rows. What is the MOST likely cause?

Accepted Answer

The data files are not in the specified S3 location.. The most likely cause is that the data files are not in the specified S3 location. When an AWS Glue table is defined in the Data Catalog, Athena reads the table's metadata (including the S3 location) and then attempts to read the underlying data files from that exact path. If the files are missing, misnamed, or in a different prefix, Athena returns zero rows because there is no data to scan. This is a common misconfiguration when the S3 path in the table definition does not match the actual data storage.

Answer

The SerDe library is incorrect for CSV files.

Answer

The table format CSV is not supported by Athena.

Answer

Athena cannot read tables from the Glue Data Catalog.

Question 9

A media company stores large video files in Amazon S3 and uses Amazon CloudFront for content delivery. Users in different regions report slow download speeds for popular content. The data engineer needs to improve performance while minimizing cost. Which solution should the engineer implement?

Accepted Answer

Enable CloudFront Origin Shield. CloudFront Origin Shield acts as a centralized caching layer in front of the S3 origin, reducing the number of requests that reach the origin and improving cache hit ratios. This minimizes latency for users in different regions by serving popular content from the edge or shield cache, while also reducing origin load and data transfer costs.

Answer

Change the S3 storage class to S3 Standard-IA

Answer

Enable S3 Transfer Acceleration on the bucket

Answer

Create multiple S3 buckets in different regions and configure CloudFront with multiple origins

Question 10

A company uses Amazon RDS for MySQL to store application data. The security team requires that all database credentials be rotated automatically every 90 days. The data engineer needs to implement a solution that minimizes operational overhead. The database credentials are stored in AWS Secrets Manager. The application retrieves the credentials at startup and caches them for the duration of the session. The application is deployed on Amazon ECS with Fargate. Which solution should the data engineer implement to meet the rotation requirement with minimal overhead?

Accepted Answer

Use Secrets Manager's automatic rotation feature with a custom Lambda function that updates the RDS password.. Secrets Manager's automatic rotation feature, combined with a custom Lambda function to update the RDS password, provides a fully automated, low-overhead solution. Option A is incorrect because Parameter Store does not natively support automatic rotation and would require additional automation. Option C is incorrect because it involves manual steps to update the application configuration, increasing operational overhead. Option D is incorrect because IAM database authentication does not rotate credentials automatically and would require significant application changes.

Answer

Store the credentials in AWS Systems Manager Parameter Store and use a scheduled job to update the password.

Answer

Create a scheduled Lambda function that updates the password in Secrets Manager and manually updates the application configuration.

Answer

Configure IAM database authentication for the RDS instance and update the application to use IAM credentials.

Question 11

The exhibit shows an S3 bucket policy. What is the effect of this policy?

Accepted Answer

Allows only GetObject and PutObject over HTTPS.. The S3 bucket policy in the exhibit uses a condition key `aws:SecureTransport` set to `true`, which restricts access to HTTPS only. The `Effect` is `Allow` for `s3:GetObject` and `s3:PutObject` actions, meaning only these two actions are permitted over HTTPS. This matches option D.

Answer

Allows all S3 actions over HTTPS only.

Answer

Allows all S3 actions to the bucket over any protocol.

Answer

Denies all S3 actions to the bucket.

Question 12

A company ingests JSON logs into Amazon S3 using Kinesis Data Firehose. The logs contain a timestamp field, but the delivery to S3 is delayed by up to 15 minutes during peak hours. The business requires near-real-time availability (under 2 minutes). Which configuration change should the data engineer make?

Accepted Answer

Decrease the buffer interval to 60 seconds. Decreasing the buffer interval to 60 seconds forces Kinesis Data Firehose to deliver data to S3 more frequently, reducing the maximum delivery latency to under 2 minutes. The default buffer interval is 300 seconds (5 minutes), and by lowering it to 60 seconds, you ensure that data is flushed to S3 within one minute of ingestion, meeting the near-real-time requirement even during peak hours when buffering might otherwise delay delivery.

Answer

Increase the number of shards in the Kinesis Data Firehose stream

Answer

Increase the buffer size to 128 MB

Answer

Enable buffering hints in the Firehose delivery stream

Question 13

A data engineer needs to ingest data from a SaaS application that sends webhooks in JSON format. The data must be stored in S3 for batch analysis. Which AWS services can receive the webhooks and store the data in S3 with minimal custom code? (Choose TWO.)

Accepted Answer

Amazon API Gateway with S3 integration. Amazon API Gateway with S3 integration (Option D) allows you to create a REST API that directly writes incoming webhook payloads to an S3 bucket without any custom code, using a proxy integration with an AWS service. This minimizes custom code because the integration handles the mapping and storage automatically.

Answer

AWS Lambda with S3 SDK

Answer

AWS Glue with a Python shell job

Answer

Amazon Kinesis Data Streams

Question 14

Refer to the exhibit. A Lambda function named 'IngestionProcessor' is failing. The engineer checks CloudWatch Logs and sees the log group exists but storedBytes is 0. Why might the logs show no data?

Accepted Answer

The Lambda execution role does not have permission to write logs to CloudWatch. The Lambda execution role must have the `logs:CreateLogStream` and `logs:PutLogEvents` permissions to write logs to CloudWatch Logs. If the role lacks these permissions, the log group will be created (if it doesn't exist) but no log events will be written, resulting in `storedBytes` being 0. This is a common misconfiguration when the IAM policy does not include the necessary CloudWatch Logs actions.

Answer

The Lambda function is configured with a dead letter queue

Answer

The Lambda function has not been invoked yet

Answer

The log group is encrypted with a KMS key and the Lambda function lacks decrypt permission

Question 15

A data engineer runs an AWS Glue ETL job that writes to a table in the AWS Glue Data Catalog. The job fails occasionally with the error 'Resource Not Found' for the table. The table exists. What is a likely cause?

Accepted Answer

The job is using an outdated version of the table schema.. AWS Glue jobs can cache the table schema at job start. If the table schema is updated while the job is running, the job may still reference the old schema version, which may no longer exist in the Data Catalog, causing a 'Resource Not Found' error even though the table exists. Option B is incorrect because concurrent writes do not cause this specific error; they may cause conflicts but not a 'Resource Not Found' for the table itself. Option C is incorrect because if the table exists and the location is wrong, it would typically result in a different error (e.g., 'Access Denied' or 'PathNotFound') rather than 'Resource Not Found' for the table. Option D is incorrect because special characters in the job name do not affect table access.

Answer

Multiple Glue jobs are writing to the same table concurrently.

Answer

The table location in S3 is incorrect.

Answer

The Glue job name contains special characters.

Question 16

A data engineer is designing a data transformation pipeline using AWS Glue. The source data is in Amazon S3 in Parquet format, and the transformed output must be written to another S3 bucket in Parquet format partitioned by year, month, day. The pipeline should handle incremental updates efficiently. Which three features should the engineer use? (Choose THREE.)

Accepted Answer

AWS Glue job bookmarks to track processed data. AWS Glue job bookmarks track processed data by recording the state of previously processed files and partitions, enabling incremental processing of new or changed data in subsequent runs. This is essential for efficiently handling incremental updates without reprocessing the entire dataset.

Answer

Use AWS Glue JobWatch for monitoring job progress

Answer

Use Spark SQL for transformations

Question 17

A data pipeline uses AWS Glue to read from an Amazon S3 bucket containing millions of small CSV files (each < 1 MB). The ETL job is slow. Which optimization would most improve performance?

Accepted Answer

Use S3 file grouping to combine small files. Using Amazon S3 file grouping or converting to columnar format like Parquet reduces the number of files and improves read performance. Increasing workers helps, but file consolidation is more impactful. Using G.1X worker type may help, but grouping files is key. Using Spark SQL directly does not address the small files problem.

Answer

Write the ETL script using PySpark instead of Scala

Answer

Increase the number of Glue workers

Answer

Use the G.1X worker type for more memory

Question 18

Which THREE factors should be considered when choosing between AWS Glue and Amazon EMR for data transformation? (Choose three.)

Accepted Answer

EMR allows fine-grained control over cluster configuration and software.. Amazon EMR provides full control over cluster configuration, including the ability to customize software, install libraries, and tune Spark, Hadoop, or Hive parameters. This fine-grained control is essential for complex or specialized data transformation pipelines that require specific versions or custom configurations.

Answer

Glue automatically stores data in S3 after transformation.

Answer

EMR supports real-time stream processing with Spark Streaming.

Question 19

A company needs to implement a data encryption strategy for data in transit between an Amazon EC2 instance and an Amazon RDS for MySQL database. Which THREE actions should be taken?

Accepted Answer

Configure the RDS instance to require SSL connections. Options A, D, and E are correct. To encrypt data in transit between EC2 and RDS MySQL, you need to enforce SSL/TLS connections. Option A configures the RDS instance to require SSL connections. Option D uses a JDBC driver with useSSL=true to enforce SSL from the client side. Option E enables the rds.force_ssl parameter in the RDS parameter group to force SSL connections at the database level. Option B is incorrect because VPC peering establishes network connectivity but does not encrypt data. Option C is incorrect because encryption at rest secures stored data, not data in transit.

Answer

Set up VPC peering between the EC2 and RDS subnets

Answer

Enable encryption at rest using KMS on the RDS instance

Question 20

A data engineer is troubleshooting a slow-running AWS Glue ETL job that reads from Amazon S3 and writes to Amazon Redshift. The job processes 500 GB of CSV data daily. The engineer wants to improve performance. Which THREE actions should the engineer take? (Choose three.)

Accepted Answer

Use a JDBC connection with a higher batch size for writing to Redshift.. Increasing the JDBC batch size for the Redshift connection reduces the number of network round trips and improves write throughput. The Glue JDBC connector batches rows into a single INSERT statement; a larger batch size (e.g., 1000 instead of the default 100) allows more rows per commit, reducing overhead and speeding up the write phase.

Answer

Switch to a single-node Redshift cluster to reduce latency.

Answer

Reduce the number of input files by combining them into larger files.