DEA-C01 Practice Test 4 — 25 Questions

Question 1

A data engineer needs to transform JSON data into CSV format using AWS Glue. The transformation is simple and must be executed on a schedule. Which Glue component is MOST suitable?

Accepted Answer

Glue ETL job. A Glue ETL job is the component designed to run transformation scripts (Spark or Python shell) on data, and it can be scheduled via triggers. For a simple JSON-to-CSV transformation on a schedule, an ETL job is the correct choice.

Answer

Glue Crawler

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Glue Data Catalog

Answer

Glue Development Endpoint

Question 2

A data engineer is designing a pipeline to ingest change data capture (CDC) events from an Amazon RDS for PostgreSQL database into Amazon S3. The CDC events are captured using AWS DMS. The data must be available for querying within 5 minutes of the change. Which approach meets these requirements?

Accepted Answer

Use AWS DMS to replicate data directly to S3 in near real-time.. AWS DMS supports continuous replication (change data capture) directly to Amazon S3 as a target endpoint. DMS can write CDC events to S3 in near real-time (typically seconds to minutes), meeting the 5-minute latency requirement without intermediate services. The data is stored in comma-separated value (CSV) or Parquet format, ready for querying via Athena or Glue.

Answer

Export the database to S3 using pg_dump and then use AWS Glue to load into S3 in Parquet format.

Answer

Use AWS DMS to replicate data to Amazon Redshift, then unload to S3.

Answer

Use AWS DMS to replicate data to an SQS queue, then process with Lambda to write to S3.

Question 3

A company uses Amazon Kinesis Data Analytics for Apache Flink to process streaming data. The application reads from a Kinesis data stream and writes results to an Amazon S3 bucket. Recently, the application has been failing with 'ResourceNotFoundException' for the S3 bucket. What is the MOST likely cause?

Accepted Answer

The S3 bucket ARN is incorrectly specified in the application configuration.. The 'ResourceNotFoundException' for the S3 bucket indicates that the application cannot find the bucket. This is most likely due to an incorrectly specified bucket name or ARN in the application configuration. If the bucket name is misspelled or the ARN is malformed, the Kinesis Data Analytics application cannot resolve the bucket resource. Option A is incorrect because missing 's3:PutObject' permission would cause an 'AccessDenied' error, not 'ResourceNotFoundException'. Option C is incorrect because the AWS Region for S3 is determined by the bucket's location, and specifying a wrong region in Flink code would typically result in a different error (e.g., 'IllegalArgumentException' or cross-region access issues) but not 'ResourceNotFoundException'. Option D is incorrect because versioning is unrelated to bucket existence; disabling versioning does not cause a resource not found error.

Answer

The IAM role used by the application does not have s3:PutObject permission.

Answer

The Flink application code specifies the wrong AWS Region for the S3 bucket.

Answer

The S3 bucket has versioning disabled.

Question 4

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 '|'.. The AWS Glue Data Catalog DDL statement uses the default 'field.delim' property, which expects comma-separated values. Since the CSV files use a pipe delimiter (|), the table will not parse rows correctly. Setting 'field.delim' to '|' in the SerDe properties tells the Hive-compatible SerDe to split on pipes instead of commas, enabling correct data ingestion.

Answer

Change the LOCATION to read from a subfolder.

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Add a partition projection configuration.

Answer

Run a crawler to detect the schema automatically.

Question 5

A data engineer is responsible for a data pipeline that uses Amazon S3 as a data lake, AWS Glue for ETL, and Amazon Athena for ad-hoc queries. The pipeline ingests CSV files from an external partner via SFTP into an S3 bucket. The files are then processed by a Glue job that converts them to Parquet and writes to a separate S3 bucket partitioned by date. The Glue job runs daily and is triggered by a scheduled CloudWatch Events rule. Recently, the data engineer noticed that some days the Glue job fails because of memory errors, and on those days the Athena queries that rely on the data return incomplete results. The engineer needs to ensure that the pipeline is resilient and that Athena queries always see a complete view of the data, even if the Glue job fails mid-run. The engineer also needs to minimize re-processing of data. Which course of action should the engineer take?

Accepted Answer

Modify the Glue job to use job bookmarks for incremental processing and write the Parquet output to a temporary location, then use an S3 copy operation to move the data into the final partitioned location only after the job completes successfully.. Writing Parquet output to a temporary location and only copying it into the final partitioned path after the job succeeds ensures Athena never sees partial data from a failed run. Job bookmarks enable incremental processing so already-processed files aren't reprocessed, minimizing re-work. This combination directly addresses both resilience (atomic visibility) and efficiency (no duplicate processing).

Answer

Increase the number of workers and the worker type to G.2X to handle the memory errors, and enable job retries.

Answer

Replace the Glue job with an AWS Lambda function that processes the CSV files and writes Parquet to S3, and use S3 Event Notifications to trigger the function.

Answer

Use Athena partition projection to automatically discover partitions and set up a retry mechanism using AWS Step Functions.

Question 6

A company has an Amazon S3 bucket with versioning enabled. They want to automatically delete noncurrent versions of objects after 30 days. Which lifecycle rule action should be used?

Accepted Answer

NoncurrentVersionExpiration. The NoncurrentVersionExpiration lifecycle action is specifically designed to remove noncurrent object versions after a specified number of days. Since versioning is enabled and the requirement is to delete noncurrent versions after 30 days, this action directly meets the goal without affecting current versions or other lifecycle aspects.

Answer

Expiration

Answer

NoncurrentVersionTransition

Answer

AbortIncompleteMultipartUpload

Question 7

A company uses Kinesis Data Analytics for SQL-based real-time analytics on streaming data. They notice that the application is processing data slower than the incoming rate, causing increased latency. Which action is MOST likely to improve the throughput?

Accepted Answer

Increase the number of Kinesis Processing Units (KPUs) for the application. Kinesis Data Analytics for SQL applications processes data using Kinesis Processing Units (KPUs), which define the compute and memory resources available. When the incoming data rate exceeds the processing capacity, increasing the number of KPUs directly scales the application's parallelism and throughput, allowing it to keep up with the stream. This is the most direct way to reduce latency caused by insufficient processing power.

Answer

Increase the number of shards in the Kinesis data stream

Answer

Enable auto-scaling on the Kinesis data stream

Answer

Decrease the retention period of the Kinesis data stream

Question 8

A company needs to store application log files for 90 days for compliance. The logs are generated continuously and are rarely accessed after 30 days. The data engineer must minimize storage costs. Which storage solution should the engineer choose?

Accepted Answer

Amazon S3 Standard with a lifecycle policy to transition to S3 Standard-IA after 30 days and expire after 90 days. Amazon S3 Standard with a lifecycle policy to transition to S3 Standard-IA after 30 days and expire after 90 days is correct because it aligns with the access pattern: logs are frequently accessed only in the first 30 days, then rarely accessed for the remaining 60 days. S3 Standard-IA offers lower storage costs for infrequently accessed data while still providing millisecond retrieval, and the lifecycle policy automates the transition and eventual deletion, minimizing costs without sacrificing availability.

Answer

Amazon CloudWatch Logs with a retention policy of 90 days

Answer

Amazon S3 Glacier Deep Archive

Answer

Amazon EBS gp3 volumes attached to an EC2 instance

Question 9

Refer to the exhibit. An IAM policy for an AWS Lambda function. The Lambda function is triggered by an S3 event (object created) and needs to read from a Kinesis stream. However, the function fails with access denied when trying to read from Kinesis. What is the most likely cause?

Accepted Answer

The Kinesis stream is encrypted with a customer managed KMS key, and the Lambda function lacks kms:Decrypt permission. When a Kinesis stream is encrypted with a customer managed KMS key, the Lambda function must have the `kms:Decrypt` permission on that key to read data from the stream. Without this permission, the Lambda function will receive an access denied error even if it has the necessary Kinesis actions (e.g., `kinesis:GetRecords`) allowed in its IAM policy. The S3 event trigger only invokes the function; it does not grant Kinesis access.

Answer

The Lambda function is not in the same region as the Kinesis stream

Answer

The Lambda function does not have permission to list S3 buckets

Answer

The S3 bucket policy denies access to the Lambda function

Question 10

A data engineer needs to transfer 50 TB of historical data from an on-premises HDFS cluster to Amazon S3. The network bandwidth is limited to 100 Mbps. The transfer must be completed within one week. Which service should be used?

Accepted Answer

AWS Snowball. AWS Snowball is the correct choice because transferring 50 TB over a 100 Mbps network would take approximately 46 days (50 TB * 8 bits/byte / 100 Mbps / 86400 seconds/day), far exceeding the one-week deadline. Snowball provides a physical storage device that can be shipped to the on-premises location, allowing data to be loaded locally and shipped to AWS, bypassing network bandwidth constraints entirely.

Answer

AWS DataSync

Answer

Amazon CloudFront

Answer

AWS Database Migration Service (DMS)

Question 11

A company uses AWS Glue to process streaming data from Amazon Kinesis Data Streams. The job fails intermittently with a 'MemoryError'. What is the MOST likely cause?

Accepted Answer

The Glue job worker type is too small for the data volume. The 'MemoryError' in AWS Glue indicates that the worker type allocated to the job does not have sufficient memory to process the data volume. Glue workers (Standard, G.1X, G.2X) have fixed memory allocations (e.g., 16 GB for Standard), and if the streaming data from Kinesis exceeds this, the job fails. Increasing the worker type or the number of workers resolves this.

Answer

The Glue job uses too many DynamicFrames

Answer

The S3 output bucket is in a different region

Answer

The Kinesis stream has insufficient shards

Question 12

A data engineer is configuring an Amazon Redshift cluster to encrypt data at rest. The company policy requires that encryption keys be stored in AWS CloudHSM. Which integration should the engineer use to meet this requirement?

Accepted Answer

Configure Redshift to use an HSM for encryption.. Amazon Redshift supports encryption at rest using either AWS KMS or a hardware security module (HSM) via CloudHSM. When company policy mandates that encryption keys be stored in AWS CloudHSM, the engineer must configure Redshift to use an HSM connection for encryption, which is the only option that satisfies the CloudHSM key storage requirement.

Answer

Use AWS KMS with a customer managed key.

Answer

Enable encryption using the AWS Redshift SSL/TLS feature.

Answer

Use Redshift automatic key rotation.

Question 13

A data engineer needs to transfer 50 TB of data from an on-premises data center to Amazon S3 over a 1 Gbps network. The transfer must be completed within one week. Which TWO AWS services can be used for this task? (Choose TWO.)

Accepted Answer

AWS DataSync. AWS DataSync is correct because it is designed to efficiently transfer large datasets over the network using a purpose-built agent that parallelizes data transfer and optimizes network utilization. With a 1 Gbps link, DataSync can transfer 50 TB within a week by leveraging its built-in compression, encryption, and incremental transfer capabilities, making it suitable for this time-constrained migration.

Answer

AWS Glue

Answer

Amazon S3 Transfer Acceleration

Answer

AWS Direct Connect

Question 14

A data engineer needs to ingest data from an on-premises Oracle database to Amazon S3 daily. The data volume is 500 GB per day, and the network bandwidth is 200 Mbps. The requirement is to minimize the impact on the source database and ensure data integrity. Which combination of AWS services should be used?

Accepted Answer

AWS Database Migration Service (DMS) with S3 as target. AWS DMS with S3 as target is correct because it supports continuous change data capture (CDC) from Oracle, minimizing impact on the source database by reading redo logs instead of querying tables directly. It can handle 500 GB/day over 200 Mbps (which yields ~2.16 TB/day theoretical max) and ensures data integrity via transactional consistency and validation checksums. DMS also automatically partitions large datasets and can resume from failures, making it ideal for daily bulk loads.

Answer

AWS Glue ETL jobs with JDBC connection

Answer

Amazon Kinesis Data Firehose with Oracle as source

Answer

AWS Data Pipeline with SQLActivity

Question 15

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. AWS Transfer Family is the most suitable service because it provides fully managed support for SFTP, FTPS, and FTP protocols, enabling direct, secure file transfers from an external FTP server to Amazon S3 without needing to manage any infrastructure. It integrates natively with S3, so files are automatically stored in the specified bucket upon transfer completion, making it ideal for daily imports of moderate data volumes.

Answer

Amazon S3 Transfer Acceleration

Answer

AWS DataSync

Answer

AWS Glue with a JDBC connection

Question 16

An application uses the 'orders' DynamoDB table with the schema and provisioned throughput shown in the exhibit. The application frequently queries by customer_id (range key) without specifying the order_id (partition key). What is the most likely impact on performance?

Accepted Answer

Queries will require a full table scan, consuming significant read capacity.. The application queries by customer_id (the sort key) without specifying order_id (the partition key). In DynamoDB, a Query operation requires the partition key to be specified; without it, the only way to retrieve items is a full table Scan, which reads every item in the table. This consumes read capacity proportional to the entire table size, leading to high latency and cost.

Answer

Queries will be throttled because the table does not have a global secondary index.

Answer

Queries will be fast because the sort key is indexed.

Answer

Queries will cause hot partitions on the table.

Question 17

A company is ingesting Apache logs from multiple web servers into AWS. The logs are sent via Amazon CloudWatch Logs to a subscription filter that delivers to a Lambda function. The Lambda function parses the logs and writes to Amazon S3. However, there is a significant backlog. Which THREE actions can reduce the backlog?

Accepted Answer

Increase the Lambda function memory allocation. Increasing the Lambda function's memory allocation also increases its CPU allocation, allowing the function to process each log event faster. This reduces the per-invocation processing time, enabling the function to handle more log data per unit time and thus reduce the backlog.

Answer

Route the CloudWatch Logs subscription to an Amazon SQS queue first

Answer

Change the Lambda function runtime from Python to Node.js

Question 18

Refer to the exhibit. A data engineer is troubleshooting an AWS Glue ETL job that fails with an access denied error when writing to S3. The IAM role attached to the Glue job has the policy shown. What is the most likely cause of the error?

Accepted Answer

The Glue job is writing to an S3 bucket that is not included in the Resource ARN. The IAM policy shown in the exhibit explicitly restricts the `s3:PutObject` action to a specific ARN pattern (e.g., `arn:aws:s3:::example-bucket/*`). If the Glue job attempts to write to a different S3 bucket—one not matching that ARN—the request will be denied with an access denied error. AWS Glue ETL jobs use the attached IAM role's permissions, and a mismatch between the target bucket and the resource ARN in the policy is the most common cause of such failures.

Answer

The Glue job is missing the s3:ListBucket permission on the bucket

Answer

The S3 bucket is encrypted with AWS KMS and the policy does not include kms:Decrypt permissions

Answer

The Glue job does not have permission to call glue:StartJobRun

Question 19

A data engineer applies the bucket policy shown in the exhibit to an S3 bucket. The bucket contains sensitive data that must be encrypted at rest and accessed only over HTTPS. Which of the following statements is true?

Accepted Answer

The policy enforces that all PutObject requests must include the x-amz-server-side-encryption header with value AES256.. The bucket policy includes a condition that denies PutObject requests unless the `s3:x-amz-server-side-encryption` header is present and set to `AES256`. This enforces server-side encryption with S3-managed keys (SSE-S3) for all uploads, ensuring data at rest is encrypted.

Answer

The policy allows both HTTP and HTTPS access.

Answer

The policy allows anonymous access to list objects in the bucket.

Answer

The policy requires the use of AWS KMS for server-side encryption.

Question 20

A company is migrating an on-premises MySQL database to Amazon RDS for MySQL. The database is 500 GB and has a 24/7 uptime requirement. The migration must minimize downtime. Which approach should be used?

Accepted Answer

Use AWS Database Migration Service (DMS) with ongoing replication to migrate the data.. AWS DMS with ongoing replication (change data capture) allows you to perform a full load of the 500 GB database and then continuously replicate changes from the on-premises MySQL source to the Amazon RDS target. This minimizes downtime because you can cut over to RDS in seconds after the target is synchronized, rather than taking the source offline for an extended period.

Answer

Take a snapshot of the on-premises database, convert it to a volume, and restore to RDS.

Answer

Export the database using mysqldump and import it into RDS using mysql command.

Answer

Create an RDS MySQL read replica from the on-premises database using native replication.