DEA-C01 Practice Exam 51 — 20 Questions

Question 1

A company wants to transform data in Amazon S3 using SQL queries without provisioning servers. The transformations are ad-hoc and run occasionally. Which service should be used?

Accepted Answer

Amazon Athena. Amazon Athena is the correct choice because it enables serverless, ad-hoc SQL querying directly on data stored in Amazon S3 without requiring any infrastructure provisioning. Since the transformations are occasional and ad-hoc, Athena's pay-per-query model and zero setup overhead align perfectly with the requirement.

Answer

AWS Glue

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Amazon Redshift Spectrum

Answer

Amazon EMR

Question 2

A data engineer is using Amazon Redshift and needs to load data from Amazon S3 into a table. The data is in Parquet format and is partitioned by date. The engineer wants to load only the latest partition and ensure that the load is efficient and cost-effective. Which method should the engineer use?

Accepted Answer

Use the COPY command with the FROM 's3://bucket/prefix/date=2023-10-01/' option to load only that partition.. The COPY command can load data directly from a specific S3 prefix, so specifying the exact partition prefix loads only that partition efficiently. This avoids unnecessary data transfer and cost. Using a WHERE clause with COPY is invalid, and alternatives like AWS Glue or Redshift Spectrum add complexity or do not load data into Redshift tables as required.

Answer

Use AWS Glue to read the Parquet data, filter by the latest date, and write to Redshift.

Answer

Use Amazon Redshift Spectrum to create an external table and query the latest partition.

Answer

Use the COPY command with the FROM 's3://bucket/prefix' option and specify the partition column in the WHERE clause.

Question 3

A CloudFormation template defines an AWS Glue job. The job fails during execution with the error 'Unable to locate script: s3://scripts-bucket/etl-script.py'. The S3 bucket 'scripts-bucket' exists and the script file is present. What is the most likely cause?

Accepted Answer

The IAM role for the Glue job does not have s3:GetObject permission on the scripts bucket.. The Glue job fails to locate the script because the IAM role assigned to the job lacks the s3:GetObject permission on the scripts-bucket. Even though the bucket and object exist, AWS Glue requires the execution role to have explicit read access to the S3 object to download and execute the script. Without this permission, the job cannot retrieve the file, resulting in the 'Unable to locate script' error.

Answer

The script location path is incorrect; it should include the bucket's region.

Answer

The Glue job requires Python version 2, but the script uses Python 3 syntax.

Answer

The S3 bucket is in a different AWS region than the Glue job.

Question 4

A company is ingesting streaming data from IoT devices into Amazon Kinesis Data Streams. The data is then processed by an AWS Lambda function that transforms the records and writes them to an Amazon S3 bucket. Recently, the Lambda function has been timing out and the S3 bucket is not receiving all expected data. The Kinesis stream is not throttling and has sufficient shards. Which step should the company take to resolve this issue?

Accepted Answer

Increase the Lambda function's timeout and memory allocation.. The Lambda function is timing out, indicating that it cannot process the records within the allotted time. Increasing the Lambda function's timeout and memory allocation (Option B) provides more execution time and CPU resources, which can help process larger or more frequent records before timing out. Option A is incorrect because reserved concurrency limits the maximum number of concurrent instances, not the execution duration of a single instance. Option C is incorrect because increasing shards is unnecessary; the stream is not throttling, and more shards do not resolve Lambda timeouts. Option D is incorrect because enhanced fan-out reduces latency for multiple consumers but does not prevent a single Lambda function from timing out due to processing time.

Answer

Increase the Lambda function's reserved concurrency.

Answer

Increase the number of shards in the Kinesis stream.

Answer

Enable enhanced fan-out on the Kinesis stream to reduce latency.

Question 5

A data engineer needs to store large volumes of infrequently accessed compliance data in Amazon S3 for 10 years. The data must be retrievable within 12 hours if required for audits. The engineer wants the most cost-effective storage solution. Which S3 storage class should be used?

Accepted Answer

S3 Glacier Deep Archive. The scenario requires long-term retention (10 years) with infrequent access and retrieval within 12 hours. S3 Glacier Deep Archive is specifically designed for this use case, offering the lowest storage cost among S3 classes while providing standard retrieval within 12 hours. It is the most cost-effective choice for compliance data that is rarely accessed.

Answer

S3 Glacier Instant Retrieval

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S3 Standard-Infrequent Access (S3 Standard-IA)

Answer

S3 Glacier Flexible Retrieval

Question 6

A data engineer is managing an Amazon Redshift cluster that experiences performance degradation during peak hours. The cluster uses a single node type and has no concurrency scaling enabled. Analysis shows that many long-running queries are queued behind short ad-hoc queries, causing delays for critical reports. The engineer needs to ensure that critical reports run promptly without affecting ad-hoc queries. Which solution meets these requirements?

Accepted Answer

Create a workload management (WLM) queue with a higher priority for critical reports and assign them to that queue.. Amazon Redshift workload management (WLM) enables you to define queues with different priorities. By routing critical reports to a high-priority queue, they are scheduled ahead of ad-hoc queries, ensuring timely execution. This approach directly addresses the need to prioritize specific workloads without impacting others.

Answer

Use short query acceleration (SQA) to run short queries in a dedicated space.

Answer

Increase the cluster size by adding more nodes to reduce overall query time.

Answer

Enable concurrency scaling to automatically add transient clusters for queued queries.

Question 7

A data engineer needs to ensure that all data in an S3 bucket is encrypted at rest. The bucket currently contains unencrypted objects from past uploads. Which action will encrypt these existing objects without re-uploading them?

Accepted Answer

Use S3 Batch Operations with an encryption job. S3 Batch Operations can run an encryption job across existing objects, applying SSE-S3, SSE-KMS, or SSE-C encryption without re-uploading the data. This is the only option that retroactively encrypts already-stored objects in place. Default encryption and bucket policies only affect new uploads, not existing objects.

Answer

Attach a bucket policy requiring SSE-S3

Answer

Enable default encryption on the bucket

Answer

Use the S3 console to select all objects and apply encryption

Question 8

A media company ingests millions of small JSON files per day into an Amazon S3 bucket. Analysts run Amazon Athena queries over this data and report that each query scans far more data than the files matching their filters, resulting in high cost and slow performance. The files are partitioned by year/month/day in S3. What should a data engineer do to reduce the data scanned per query?

Accepted Answer

Convert the JSON files to Apache Parquet, store them in the existing partition structure, and define the table in the AWS Glue Data Catalog with the correct partition columns.. Athena's cost model is based on bytes scanned, so the most effective optimization is to store data in a columnar format such as Parquet and rely on partition pruning. Parquet enables column projection and predicate pushdown, while year/month/day partitions let Athena skip entire prefixes. Together they sharply reduce scanned bytes, cutting cost and improving query speed for the analyst workload.

Answer

Move the files into an Amazon Redshift cluster using COPY and query them with Redshift Spectrum.

Answer

Create an Amazon CloudFront distribution in front of the S3 bucket and run Athena against the distribution.

Answer

Enable S3 Transfer Acceleration on the bucket and increase the Athena query timeout.

Question 9

A data engineer is setting up an Amazon DynamoDB table to store user session data. The table must handle sudden spikes in read traffic during peak hours, and the engineer wants to minimize operational overhead while ensuring consistent performance. The table's read capacity mode should automatically adjust to traffic changes. Which capacity mode should the engineer choose?

Accepted Answer

On-demand capacity mode.. On-demand capacity mode is designed for workloads with unpredictable traffic patterns. It automatically scales to handle sudden spikes in read and write traffic, eliminating the need for capacity planning and reducing operational overhead. This makes it the best choice for session data with variable demand.

Answer

Provisioned capacity mode with global secondary indexes.

Answer

Provisioned capacity mode with auto scaling enabled.

Answer

Provisioned capacity mode with reserved capacity.

Question 10

A company stores application logs in an Amazon S3 bucket. A compliance policy states that log objects must be retained for exactly 90 days and then permanently deleted, and that no one, including administrators, should be able to delete them earlier. The data engineer must enforce this with the least effort. What should the engineer do?

Accepted Answer

Apply an S3 Object Lock retention period of 90 days in compliance mode to the bucket, and configure a lifecycle rule to expire objects after 90 days.. S3 Object Lock in compliance mode provides WORM protection that even the root user cannot override before the retention period ends, which satisfies the immutability requirement. Pairing it with a lifecycle rule that expires objects after 90 days ensures automatic permanent deletion at the required time. Together they enforce the compliance policy with minimal operational effort.

Answer

Create an S3 Lifecycle rule that transitions objects to S3 Glacier Deep Archive after 90 days.

Answer

Use AWS Backup to create a vault with a 90-day retention and a vault lock in compliance mode.

Answer

Enable S3 Versioning and add a bucket policy that denies s3:DeleteObject to all principals.

Question 11

A data engineer is setting up Amazon S3 event notifications to trigger an AWS Lambda function when new objects are uploaded. Which TWO actions are required to enable this?

Accepted Answer

Add a resource-based policy to the Lambda function to allow S3 to invoke it.. Lambda functions use a resource-based policy (also known as a function policy) to grant permissions to other AWS services, such as S3, to invoke the function. Without this policy, S3 will receive an access denied error when trying to trigger the Lambda function. Option D is correct because you must configure an S3 event notification on the bucket for the `s3:ObjectCreated:*` event type to instruct S3 to send a notification to the Lambda function when new objects are uploaded.

Answer

Enable S3 versioning on the bucket.

Answer

Create an S3 bucket policy that grants S3 permission to invoke Lambda.

Answer

Set up an Amazon CloudWatch Events rule to detect S3 uploads.

Question 12

A company uses AWS Glue ETL jobs to transform data in Amazon S3. The data arrives in JSON format but needs to be converted to Parquet for efficient querying. Which AWS Glue feature should be used to infer the schema and generate transformation code?

Accepted Answer

AWS Glue crawlers. AWS Glue crawlers are the correct feature because they automatically connect to data stores (like S3), infer the schema of JSON data by sampling it, and populate the AWS Glue Data Catalog with table definitions. This catalog schema can then be used by AWS Glue ETL jobs to generate transformation code (e.g., converting JSON to Parquet) without manual schema definition.

Answer

Amazon S3 Select

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Amazon Athena

Answer

Amazon Kinesis Data Analytics

Question 13

A data engineer needs to store semi-structured JSON event logs in a data lake on Amazon S3 and query them with Amazon Athena using SQL, including filtering on individual JSON attributes. The team wants to avoid transforming the files before querying. Which approach should the engineer use?

Accepted Answer

Define an Athena table with a struct or map column over the JSON and query nested fields. Athena queries data in place on S3 using table definitions in the AWS Glue Data Catalog. For semi-structured JSON, defining columns as struct, array, or map with the appropriate JSON SerDe lets SQL access nested attributes directly without preprocessing. Storing as CSV would require flattening, loading into Redshift adds a transformation step, and CloudWatch Logs Insights is scoped to log groups rather than the S3 data lake.

Answer

Store the logs as CSV and use Athena to parse the columns

Answer

Use Amazon CloudWatch Logs Insights to query the JSON logs in place

Answer

Load the JSON into Amazon Redshift using COPY JSON and query it there

Question 14

A data engineer is building an Amazon Redshift data warehouse that ingests large staged files from Amazon S3 using the COPY command. The team wants to maximize load performance and minimize the time spent on ingestion. Which TWO practices should the engineer apply? (Choose two.)

Accepted Answer

Load compressed columnar files such as Parquet in a single COPY statement. COPY performance in Redshift depends on parallelism and data volume. Splitting input into multiple similarly sized files lets every slice read concurrently, and using compressed columnar formats such as Parquet reduces bytes moved and enables column pruning. Together these practices shorten load time. Sort keys, single-file loads, and post-load VACUUM operations affect query performance or add overhead rather than accelerating ingestion, so they do not belong in this optimization.

Answer

Run VACUUM SORT ONLY on the target table immediately after each COPY

Answer

Use a single large compressed file to reduce the number of S3 GET requests

Answer

Add a sort key to the target table on the timestamp column before loading

Question 15

A data engineer is building a data lake on Amazon S3 and must enforce that all objects containing personally identifiable information are encrypted with a customer managed AWS KMS key, while allowing automatic key rotation and audit of key usage. Objects must remain readable by an AWS Glue job and an Amazon Athena workgroup. Which configuration should the engineer choose?

Accepted Answer

SSE-KMS with a customer managed key, key rotation enabled, and bucket policy enforcing the key. A customer managed KMS key with SSE-KMS satisfies control, rotation, and auditability: the key policy scopes who may use it, automatic rotation can be enabled, and CloudTrail logs every Encrypt, Decrypt, and GenerateDataKey call. A bucket policy that denies noncompliant uploads enforces the standard, and granting the Glue role and Athena workgroup decrypt permissions keeps analytics working. AWS managed keys and SSE-S3 cannot meet the customer control and rotation requirements.

Answer

Client-side encryption with an application managed key stored in the application code

Answer

SSE-KMS with the AWS managed key aws/s3 and default bucket encryption

Answer

SSE-S3 with bucket versioning enabled

Question 16

A data engineering team is building a data lake on Amazon S3. They need to catalog data and make it queryable by Amazon Athena and Amazon Redshift Spectrum. The data arrives in multiple formats and the schema evolves frequently. Which TWO actions should the team take to support schema evolution and efficient querying? (Choose two.)

Accepted Answer

Define tables in the AWS Glue Data Catalog and use AWS Glue crawlers to infer and update schemas as new data arrives.. The AWS Glue Data Catalog with crawlers keeps table and partition metadata current as schemas evolve, and both Athena and Redshift Spectrum read from it. Using open columnar formats such as Parquet or ORC with partitioned prefixes enables column projection and partition pruning, which cut scanned bytes and cost. Together, these two actions support evolving schemas and efficient querying across both engines.

Answer

Store all data as uncompressed CSV to maximize compatibility with all query engines.

Answer

Create a separate S3 bucket for each schema version and require analysts to query the correct bucket manually.

Answer

Enable S3 Object Lock on the data lake bucket to preserve schema versions.

Question 17

A data engineer stores application logs in an Amazon S3 bucket. Compliance requires that log objects be retained for seven years and that they cannot be deleted or overwritten by any user, including the account root user, during that period. The engineer must configure the bucket to enforce this. Which combination of settings should the engineer apply?

Accepted Answer

Enable S3 Object Lock in compliance mode with a default retention period of seven years on the bucket.. S3 Object Lock provides write-once-read-many protection at the object version level. Compliance mode is the strictest setting: no principal, including the account root user, can delete or overwrite a locked version before retention expires. Applying a bucket default retention of seven years automatically protects newly uploaded log objects without per-object calls, meeting the compliance requirement.

Answer

Enable S3 Object Lock in governance mode and grant the s3:BypassGovernanceRetention permission only to the root user.

Answer

Enable S3 Versioning and attach a bucket policy that denies s3:DeleteObject to all principals except the root user.

Answer

Configure an S3 Lifecycle rule to transition objects to S3 Glacier Deep Archive after one day and expire them after seven years.

Question 18

A company runs a critical PostgreSQL database on Amazon RDS. The database experiences high read latency during peak hours. The data engineer needs to reduce read latency with minimal changes to the application. Which solution is MOST effective?

Accepted Answer

Create a read replica of the RDS instance and redirect read queries to it.. A read replica is a separate RDS instance that receives asynchronous replication from the primary. By redirecting read-only queries to the replica, you offload read traffic from the primary, directly reducing read latency during peak hours. This requires minimal application changes—typically just updating the connection string for read operations. Multi-AZ and larger instance classes do not provide a dedicated read-scaling endpoint, and deleting indexes would harm performance.

Answer

Delete unused indexes to improve query performance.

Answer

Enable Multi-AZ deployment for automatic failover.

Answer

Increase the DB instance class to a larger size with more memory.

Question 19

A company is using an Amazon RDS for MySQL database for an e-commerce application. During a sales event, the database experiences high read traffic, causing slow query performance. The company wants to reduce the read load on the primary database without changing the application code. Which solution meets these requirements?

Accepted Answer

Create an Amazon RDS read replica and direct read traffic to it.. An Amazon RDS read replica is a read-only copy of the primary database that can offload read traffic without requiring any application code changes. By directing read queries to the replica, the primary database's load is reduced, improving performance during high-read events. This solution is specifically designed for read-heavy workloads and integrates seamlessly with existing MySQL connections.

Answer

Enable Multi-AZ on the RDS instance.

Answer

Increase the instance size of the RDS database.

Answer

Deploy Amazon ElastiCache to cache query results.

Question 20

A data engineer must choose a storage service for a new application that requires single-digit millisecond latency at any scale, a flexible schema, and automatic scaling of throughput without provisioning capacity. The access pattern is key-value lookups by user ID with occasional range queries on a sort key. Which AWS service should the engineer select?

Accepted Answer

Amazon DynamoDB with on-demand capacity mode. DynamoDB is purpose-built for key-value and document workloads needing consistent single-digit millisecond latency at any scale. A partition key on user ID serves point lookups, and a sort key supports efficient range queries. On-demand capacity mode removes provisioning and scales automatically with traffic, while the flexible schema accommodates evolving attributes without migrations, matching every stated requirement.

Answer

Amazon RDS for PostgreSQL with automatic storage scaling

Answer

Amazon S3 with S3 Select

Answer

Amazon Redshift with a distribution key on user ID