DEA-C01 Mock Exam 93 — 25 Questions

Question 1

A company is using AWS Glue to run ETL jobs that read from Amazon S3 and write to Amazon Redshift. The jobs are failing intermittently with 'Out of Memory' errors. Which TWO actions should the data engineer take to resolve this issue? (Choose TWO.)

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

Accepted Answer

Increase the number of DPUs allocated to the Glue job. Increasing the number of DPUs allocated to the Glue job (Option B) directly addresses the 'Out of Memory' errors by providing more memory and compute resources per executor. AWS Glue uses Apache Spark under the hood, where each DPU provides 4 vCPU and 16 GB of memory; adding more DPUs increases the total memory available for data processing, reducing the likelihood of OOM errors during shuffle or aggregation operations.

Answer

Switch the output to Amazon S3 instead of Redshift

Answer

Reduce the number of partitions in the input data

Answer

Increase the spark.sql.shuffle.partitions parameter

Question 2

A financial services company stores sensitive transaction data in an Amazon S3 bucket. Compliance requires that all objects be encrypted using SSE-KMS and that the bucket be protected from accidental deletion. Which combination of actions meets these requirements? (Select TWO.)

Accepted Answer

Add a bucket policy that denies PutObject if the object is not encrypted with SSE-KMS. A bucket policy with a condition denying PutObject unless the object's encryption status matches SSE-KMS (using the s3:x-amz-server-side-encryption-aws-kms-key-id condition key) enforces encryption at the upload level. This ensures that any object written to the bucket must be encrypted with a KMS key, meeting the compliance requirement.

Answer

Enable MFA Delete on the bucket

Answer

Enable S3 Block Public Access

Answer

Set default encryption to SSE-S3

Question 3

A company is using Amazon ElastiCache for Redis to cache frequently accessed data. The cache hit ratio is low, and the engineering team suspects that the eviction policy is causing important data to be removed. Which eviction policy should be used to minimize eviction of the most frequently accessed keys?

Accepted Answer

allkeys-lfu. The allkeys-lfu (Least Frequently Used) eviction policy is the correct choice because it explicitly tracks and retains keys that are accessed most frequently across the entire keyspace. Since the cache hit ratio is low due to eviction of important data, LFU ensures that frequently accessed keys are evicted last, directly addressing the problem of important data being removed.

Answer

allkeys-lru

Answer

noeviction

Answer

volatile-lru

Question 4

A data engineering team is building a data lake on Amazon S3. They need to ingest data from multiple sources: (1) streaming IoT data, (2) daily CSV exports from an on-premises system via SFTP, and (3) change data capture (CDC) from an Amazon Aurora database. Which THREE services should the team use to ingest these data sources?

Accepted Answer

Amazon Kinesis Data Streams for IoT data ingestion.. Amazon Kinesis Data Streams is purpose-built for real-time streaming data ingestion, making it ideal for IoT data that arrives continuously. It can capture and store data streams for processing by consumers like Kinesis Data Analytics or Lambda, providing low-latency ingestion and durable storage.

Answer

AWS Glue ETL for CDC from Aurora.

Answer

Amazon EMR for daily CSV ingestion.

Question 5

A data engineer runs the AWS CLI command shown in the exhibit to list objects in an S3 bucket. The command returns only two objects even though the bucket contains thousands of objects under the prefix. What should the engineer do to retrieve the next batch of objects?

Accepted Answer

Use the --starting-token parameter with the value from the NextToken field.. The AWS CLI `list-objects-v2` command paginates results by default. When the output is truncated, the response includes a `NextToken` field. To retrieve the next batch, the engineer must use the `--starting-token` parameter with the value from that `NextToken` field, which tells the CLI to resume listing from where it left off.

Answer

Increase the --max-items value to a larger number.

Answer

Use the --page-size parameter to request more items per API call.

Answer

Change the --prefix to a more specific value.

Question 6

A data engineer notices that an Amazon Redshift cluster's storage utilization has grown unexpectedly. The cluster uses automatic compression and has a mix of fact and dimension tables. The engineer runs VACUUM and ANALYZE, but storage does not decrease. Which action is most likely to reduce storage consumption?

Accepted Answer

Perform a DEEP COPY on the largest tables.. DEEP COPY recreates the table with a fresh, optimally sorted and compressed storage layout, reclaiming space that VACUUM alone cannot recover. In Redshift, VACUUM reorganizes and reclaims space from deleted rows but does not re-apply compression or rebuild the underlying storage blocks; DEEP COPY (e.g., using CREATE TABLE AS or the DEEP COPY command) physically rewrites the data, eliminating fragmentation and applying the current compression encoding, which can significantly reduce storage consumption when automatic compression has left suboptimal encodings or when historical updates have bloated the table.

Answer

Run VACUUM with the BOOST option.

Answer

Run ANALYZE with the FULL keyword on all tables.

Answer

Modify the sort key on the largest tables to a more selective column.

Question 7

Which THREE actions can help improve read performance in Amazon DynamoDB? (Choose THREE.)

Accepted Answer

Use parallel scans to distribute read load across partitions.. Parallel scans in DynamoDB can improve read performance by dividing a scan operation into multiple segments that are processed concurrently across partitions. This reduces the overall latency of the scan by leveraging the distributed nature of DynamoDB's storage, though it consumes more read capacity units (RCUs) due to the parallel execution.

Answer

Use DynamoDB global tables to replicate data.

Answer

Use strongly consistent reads for all queries.

Question 8

A data engineer is ingesting streaming data from thousands of IoT devices into AWS. The data is JSON-formatted and must be stored in Amazon S3 for long-term analytics. Which service is most appropriate for real-time ingestion and routing to S3?

Accepted Answer

Amazon Kinesis Data Firehose. Amazon Kinesis Data Firehose is the most appropriate service because it is designed for real-time ingestion of streaming data and can directly deliver data to Amazon S3 without requiring custom code. It automatically handles buffering, compression, and partitioning of JSON data, making it ideal for long-term analytics storage.

Answer

Amazon SQS

Answer

Amazon Kinesis Data Streams

Answer

AWS Glue

Question 9

Match each AWS Glue component to its role.

Accepted Answer

Data Catalog: Central metadata repository for storing table definitions and schema.. AWS Glue components work together for ETL. The Data Catalog stores metadata, Crawlers populate the catalog, Classifiers infer schema, and ETL Jobs execute transformations. Connections provide connectivity but are not listed here.

Answer

Data Catalog: Executes transformation scripts.

Answer

Crawler: Stores configuration for connecting to data stores.

Question 10

Match each AWS data migration tool to its primary function.

Accepted Answer

AWS Database Migration Service (DMS): Migrates databases to AWS with minimal downtime. AWS DMS migrates databases with minimal downtime; AWS Snowball transfers large datasets physically; AWS DataSync automates online data transfer. Common confusions include swapping tool functions or attributing schema conversion to DataSync instead of SCT.

Answer

AWS Database Migration Service (DMS): Transfers large datasets via physical devices

Answer

AWS Snowball: Migrates databases to AWS with minimal downtime

Answer

AWS DataSync: Converts database schema to target platform

Question 11

Match each AWS monitoring tool to its primary use.

Accepted Answer

CloudWatch: Monitor metrics, logs, and alarms. CloudWatch monitors metrics and logs, CloudTrail audits API calls, X-Ray traces requests, and Trusted Advisor provides optimization recommendations. Common confusions include swapping the roles of CloudWatch and CloudTrail.

Answer

CloudWatch: Auditing API activity

Answer

CloudTrail: Monitor metrics, logs, and alarms

Question 12

Arrange the steps to implement data encryption at rest for an Amazon Redshift cluster using AWS KMS.

Accepted Answer

Step 1: Create a KMS key. Step 2: Launch a new Amazon Redshift cluster. Step 3: Enable encryption and specify the KMS key during launch. Step 4: Verify that the cluster is encrypted at rest.. First, create the KMS key. Then launch a new encrypted cluster, specify the key, configure, and verify encryption.

Answer

Step 1: Launch a new Amazon Redshift cluster. Step 2: Create a KMS key. Step 3: Enable encryption and specify the KMS key. Step 4: Verify encryption.

Answer

Step 1: Create a KMS key. Step 2: Verify encryption. Step 3: Launch a new Amazon Redshift cluster. Step 4: Enable encryption and specify the KMS key.

Answer

Step 1: Specify the KMS key. Step 2: Create a KMS key. Step 3: Launch a new Amazon Redshift cluster. Step 4: Verify encryption.

Question 13

A company uses AWS Glue ETL jobs to transform data stored in Amazon S3. The job reads data in Parquet format, applies transformations, and writes the output back to S3 in Parquet format. The team wants to improve the job's performance and reduce costs. Which action is MOST effective?

Accepted Answer

Use column pruning and predicate pushdown to read only necessary columns and filter data early.. Column pruning and predicate pushdown reduce the amount of data read from S3 by Spark-based AWS Glue ETL jobs. By reading only the necessary columns and filtering rows early in the scan, I/O and memory usage decrease, directly improving performance and reducing costs.

Answer

Change the input format from Parquet to CSV to simplify parsing.

Answer

Coalesce the input data into a single large file before processing.

Answer

Increase the number of workers to maximum allowed.

Question 14

A company uses Amazon Kinesis Data Firehose to deliver data to Amazon S3. The data engineer needs to transform the data before delivery. Which THREE options can be used to perform the transformation?

Accepted Answer

Amazon Kinesis Data Firehose data format conversion (e.g., JSON to Parquet). Amazon Kinesis Data Firehose can transform data natively using data format conversion (e.g., converting JSON to Parquet or ORC) without requiring external services. This is a built-in capability that applies schema-based conversion using AWS Glue tables, enabling efficient storage and querying in Amazon S3.

Answer

Amazon Athena queries

Answer

AWS Glue ETL job

Question 15

A company is ingesting streaming data from a fleet of weather sensors. Each sensor sends a JSON payload every second. The data is used for real-time dashboarding and also archived to S3. The pipeline should handle sudden bursts of data without data loss. Which architecture meets these requirements?

Accepted Answer

Amazon Kinesis Data Streams -> AWS Lambda for dashboard -> Amazon Kinesis Data Firehose -> S3. Kinesis Data Streams provides durable, scalable ingestion that can handle sudden bursts of data without loss, while Lambda processes records for real-time dashboarding and Kinesis Data Firehose reliably buffers and archives data to S3. This decoupled architecture ensures no data is lost even during traffic spikes, as Kinesis Data Streams retains data for up to 365 days and Firehose can buffer incoming records before writing to S3.

Answer

Amazon EC2 with Apache Kafka -> S3

Answer

Amazon Kinesis Data Firehose directly with no buffer

Answer

Amazon SQS -> AWS Lambda -> S3

Question 16

A company uses AWS Glue to process sensitive data stored in Amazon S3. The security team requires that all data in transit between AWS Glue and S3 be encrypted. Which configuration should be used to meet this requirement?

Accepted Answer

Use an S3 bucket policy that denies requests not using HTTPS.. Requiring HTTPS for all requests to the S3 bucket ensures that data in transit between AWS Glue and S3 is encrypted using TLS. By using an S3 bucket policy with a condition that denies requests where `aws:SecureTransport` is false, the company enforces encryption for all connections, including those from AWS Glue. This meets the security requirement without needing to modify Glue or S3 configurations beyond the bucket policy.

Answer

Use an AWS KMS key to encrypt the data before uploading to S3.

Answer

Configure AWS Glue to use SSL by setting the 'ssl' parameter to 'true'.

Answer

Enable default encryption on the S3 bucket using SSE-S3.

Question 17

A company uses AWS Glue to run ETL jobs that process data from an Amazon RDS for MySQL database and load it into an Amazon S3 data lake. The Glue job runs daily and processes incremental data. Recently, the job has been taking longer than expected. The engineer checks the CloudWatch logs and sees that the job is spending most of its time on the 'Reading from JDBC' phase. The MySQL table has 10 million rows and is indexed on the primary key. The Glue job uses a 'job bookmark' to track processed data. The engineer wants to improve the performance of the read phase. Which action is most likely to help?

Accepted Answer

Modify the job to use a 'query' parameter that selects only the new or modified rows based on a timestamp column.. Modifying the job to use a 'query' parameter with a WHERE clause that filters on a timestamp column (the bookmark key) allows AWS Glue to read only the new or modified rows, reducing the amount of data transferred from the database and significantly improving read performance. Option A is wrong because increasing the JDBC 'fetchSize' parameter can improve throughput per connection but does not address the root cause of reading all 10 million rows; it may also cause memory issues if set too high. Option B is wrong because disabling job bookmarks and performing a full refresh would reprocess all data, making the job even slower and defeating the purpose of incremental processing. Option C is wrong because increasing the number of DPUs adds parallelism but does not reduce the volume of data read; the database can still become a bottleneck when reading the entire table.

Answer

Increase the JDBC 'fetchSize' parameter to 10000.

Answer

Disable job bookmark and perform a full refresh each time.

Answer

Increase the number of DPUs for the Glue job.

Question 18

A multinational corporation uses AWS Organizations to manage multiple accounts. The data engineering team has a central data lake account that stores all data in S3. The security team requires that all cross-account access to the data lake be logged and that any access from outside the organization be blocked. The team has enabled S3 server access logs and AWS CloudTrail. However, they notice that some requests from an external AWS account are still able to read data from the data lake. The bucket policy currently allows cross-account access to a specific partner account for data exchange. What additional step should the team take to block access from all other external accounts?

Accepted Answer

Add a Deny statement to the bucket policy that denies access to any principal not in the organization or the partner account.. To block access from all external accounts except the allowed partner, you can add a Deny statement with a condition that checks if the account is not in the organization and not the partner account. Option A is wrong because disabling cross-account access would block the partner. Option B is wrong because the bucket policy already allows the partner. Option D is wrong because S3 Access Points do not inherently block external accounts unless explicitly configured.

Answer

Add a condition to the existing Allow statement to require that the source account be in the organization.

Answer

Remove the cross-account access statement from the bucket policy.

Answer

Use S3 Access Points to restrict access to only the partner account.

Question 19

Refer to the exhibit. A data engineer runs an AWS Glue ETL job that writes output to an S3 bucket. The job fails with the error shown. What is the most likely cause?

Accepted Answer

The IAM role used by the Glue job lacks the s3:PutObject permission for the output bucket. The error shown in the exhibit indicates an access denied or permission failure when the AWS Glue ETL job attempts to write its output to the S3 bucket. The most likely cause is that the IAM role assigned to the Glue job does not include the s3:PutObject permission for the target bucket, which is required to upload objects. Without this permission, the job cannot complete the write operation, resulting in the failure.

Answer

The Glue job attempted to write data in an unsupported format

Answer

The S3 bucket does not exist

Answer

The output file name contains invalid characters

Question 20

Which THREE are best practices for managing data in Amazon S3 for a data lake? (Choose three.)

Accepted Answer

Enable S3 Versioning to protect against accidental deletions.. Enabling S3 Versioning is a best practice for data lakes because it protects against accidental deletions or overwrites by preserving all versions of an object, including deletions (which are recorded as delete markers). This allows you to recover previous object states and is essential for data governance and auditability in a data lake environment.

Answer

Enable S3 Snapshot for point-in-time recovery.

Answer

Disable S3 server access logging to reduce costs.