DEA-C01 Data Store Management Practice Test 30 — 15 Questions

Question 1

A company runs a production Amazon RDS for PostgreSQL database. The database is experiencing performance degradation due to a high number of concurrent read queries. The data engineer needs to improve read performance without significantly increasing costs. Which TWO actions should the engineer take? (Choose TWO.)

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

Accepted Answer

Create one or more read replicas in the same region.. Creating one or more read replicas in the same region offloads read traffic from the primary DB instance, directly addressing the high number of concurrent read queries. Read replicas are asynchronous copies that can serve SELECT traffic, improving read throughput without increasing the cost of the primary instance. This is a cost-effective scaling strategy because you pay only for the replica instances and can choose smaller instance sizes if read workloads are bursty.

Answer

Enable Multi-AZ deployment for automatic failover.

Answer

Increase the allocated storage size to improve IOPS.

Answer

Delete unnecessary indexes to reduce write overhead.

Question 2

A data engineer is using Amazon DynamoDB to store session data for a web application. The engineer wants to ensure that all data is encrypted at rest using an AWS managed key. Which step should the engineer take to achieve this?

Accepted Answer

Create the DynamoDB table with encryption at rest enabled using an AWS managed key. [CORRECT]. Only option E is correct. DynamoDB encryption at rest is enabled by default for new tables using an AWS managed key (aws/dynamodb). Creating the table with encryption at rest enabled using an AWS managed key ensures all data is encrypted with a key managed by AWS. Option C is incorrect because specifying a customer managed key would override the default AWS managed key, which does not meet the requirement to use an AWS managed key. Options A, B, and D are incorrect: SSE-S3 is for S3, disabling encryption is unsafe and does not meet the requirement, and client-side encryption is separate from at-rest encryption.

Answer

Enable server-side encryption with S3-managed keys (SSE-S3) on the DynamoDB table. [wrong]

Answer

Disable encryption at rest to improve performance. [wrong]

Answer

Specify an AWS KMS customer managed key for encryption if required. [wrong]

Answer

Use client-side encryption before writing data to DynamoDB. [wrong]

Question 3

A company uses Amazon S3 to store log files that are generated every hour. Each log file is about 1 GB. The logs must be stored for 5 years for compliance. The data engineer wants to minimize storage costs while ensuring that logs can be retrieved within 24 hours for the first year, and within 48 hours thereafter. Which TWO lifecycle actions should the engineer configure? (Choose TWO.)

Accepted Answer

Transition objects to S3 Glacier Deep Archive after 1 year.. Transitioning objects to S3 Glacier Deep Archive after 1 year provides the lowest storage cost while meeting the 5-year retention requirement. After the first year, the retrieval window of up to 48 hours for Glacier Deep Archive satisfies the compliance need. Option E is correct because after 30 days, logs are less frequently accessed but still need retrieval within 24 hours during the first year; S3 Standard-IA offers lower cost than S3 Standard for such infrequent access. Option A is incorrect because transitioning to S3 Standard after 30 days is more expensive than Standard-IA and does not provide cost savings. Option C is incorrect because 'Set a retrieval window of 48 hours for Glacier Deep Archive' is not a lifecycle action; retrieval windows are configured during restore operations, not in lifecycle rules. Option D is incorrect because deleting objects after 2 years violates the 5-year retention policy.

Answer

Transition objects to S3 Standard after 30 days.

Answer

Set a retrieval window of 48 hours for Glacier Deep Archive.

Answer

Delete objects after 2 years to reduce storage costs.

Question 4

A data engineer at a media company is managing an Amazon RDS for MySQL database that stores user profiles and preferences. The database has been running on a db.r5.large instance with 500 GB of General Purpose SSD (gp2) storage. Recently, the application team has noticed increased query latency during peak hours. Amazon CloudWatch metrics show that the ReadIOPS metric is consistently peaking at 5,000 IOPS, which is near the baseline performance of the gp2 volume (1,500 IOPS baseline for 500 GB, but with bursts up to 3,000 IOPS for short periods). The database is not CPU-bound, and memory utilization is moderate. The data engineer needs to resolve the I/O bottleneck with minimal cost increase. The company is open to changing the storage type or instance class, but wants to avoid over-provisioning. What should the data engineer do?

Accepted Answer

Change the storage type to General Purpose SSD (gp3) and set the provisioned IOPS to 5,000.. Gp3 provides a baseline of 3,000 IOPS at no additional cost and allows provisioning additional IOPS independently. Setting provisioned IOPS to 5,000 gives the required performance without the burst limitations of gp2 and at a lower cost than io1. Option B is incorrect because Multi-AZ does not improve read IOPS; the standby is not used for reads. Option C is incorrect because io1 would be more expensive than gp3 for the same IOPS. Option D is incorrect because upgrading the instance class adds memory and compute, which does not directly improve IOPS, and would increase cost unnecessarily.

Answer

Enable Multi-AZ deployment to offload reads to the standby instance.

Answer

Change the storage type to Provisioned IOPS SSD (io1) and provision 5,000 IOPS.

Answer

Upgrade the instance to a db.r5.xlarge to get more memory and reduce I/O.

Question 5

A startup is building a ride-sharing application that uses Amazon DynamoDB to store trip data. The table has a partition key of 'trip_id' and a sort key of 'status'. The application writes a new item when a trip starts and updates the status when the trip ends. The development team is experiencing high write latency during peak hours. The table is provisioned with 5,000 write capacity units (WCU) and 5,000 read capacity units (RCU). CloudWatch metrics show that WriteThrottleEvents are occurring frequently, but the consumed write capacity is never above 4,000 WCU. The team suspects that the issue is due to hot partitions. How should the data engineer resolve this issue?

Accepted Answer

Modify the application to add a random suffix to the partition key when writing items.. Adding a random suffix to the partition key distributes writes across multiple partitions, preventing any single partition from becoming a hot spot and causing throttling. Option B is incorrect because DAX is an in-memory cache that speeds up reads, not writes; it does not address write throttling. Option C is incorrect because decreasing RCU does not affect write performance; write throttling is independent of read capacity. Option D is incorrect because increasing WCU does not solve hot partition issues; throttling occurs at the partition level, and a single partition can only handle up to 1000 WCU per partition. Thus, distributing writes is the appropriate solution.

Answer

Enable DynamoDB Accelerator (DAX) to cache write operations.

Answer

Decrease the provisioned RCU to 2,000 to reduce costs.

Answer

Increase the provisioned WCU to 10,000 to handle the spikes.

Question 6

A company uses Amazon S3 to store sensitive documents. The security team has mandated that all objects must be encrypted at rest using server-side encryption with AWS KMS (SSE-KMS). Additionally, the company wants to ensure that any attempt to upload an unencrypted object is denied. A data engineer has configured a bucket policy that denies PutObject if the encryption header does not include x-amz-server-side-encryption: aws:kms. However, the engineer notices that some objects are still being stored without encryption. Upon investigation, the engineer suspects that the policy is not being evaluated correctly. What should the engineer do to ensure that all objects are encrypted with SSE-KMS?

Accepted Answer

Enable default encryption on the S3 bucket with SSE-KMS.. Enabling default encryption on the S3 bucket with SSE-KMS ensures that any object uploaded without an explicit encryption header is automatically encrypted with SSE-KMS. This closes the gap where the bucket policy condition fails to catch uploads that omit the `x-amz-server-side-encryption` header entirely, as the policy only denies requests with an incorrect header but does not block requests that lack the header altogether. Default encryption applies server-side encryption at the bucket level, making it impossible to store an unencrypted object.

Answer

Use an IAM policy to require encryption instead of a bucket policy.

Answer

Enable S3 Block Public Access settings.

Answer

Add a condition to the bucket policy that checks for aws:SourceVpce.

Question 7

A company is designing a data lake on AWS using Amazon S3. The data includes sensitive customer information that must be encrypted at rest. The company requires that encryption keys be managed by AWS, but the keys must be rotated automatically every year. Which TWO options meet these requirements? (Choose TWO.)

Accepted Answer

Use Server-Side Encryption with Amazon S3-Managed Keys (SSE-S3).. SSE-S3 is correct because it provides server-side encryption where AWS manages the encryption keys entirely, including automatic annual rotation. This meets the requirement of encryption at rest with AWS-managed keys and automatic yearly rotation without any additional configuration.

Answer

Use client-side encryption with an AWS KMS key.

Answer

Use Server-Side Encryption with Customer-Provided Keys (SSE-C).

Answer

Use Server-Side Encryption with AWS KMS-Managed Keys (SSE-KMS) with manual key rotation.

Question 8

A company uses Amazon Redshift for its data warehouse. The cluster has multiple node types and is configured with automated snapshots. The company needs to ensure high availability and disaster recovery across AWS Regions. Which THREE actions should the company take to meet these requirements? (Choose THREE.)

Accepted Answer

Restore a snapshot from the secondary Region in the event of a disaster.. Restoring a snapshot from a secondary Region is the core disaster recovery action in a cross-Region DR strategy. When a primary Region fails, you can restore the cross-Region snapshot copy to a new Redshift cluster in the secondary Region, ensuring business continuity. This leverages the automated cross-Region copy configured in Option E to make the snapshot available in the DR Region.

Answer

Enable automated snapshots with a retention period of at least 1 day.

Answer

Create manual snapshots on a daily basis and copy them to another Region.

Question 9

A data engineer needs to store streaming data from multiple sources into Amazon S3. The data should be organized by source, date, and hour. The engineer wants to minimize processing overhead. Which THREE S3 features should the engineer use to achieve this? (Choose THREE.)

Accepted Answer

S3 Inventory to list objects and their metadata.. S3 prefixes organize objects into a hierarchy. S3 Inventory provides a list of objects. S3 Event Notifications trigger downstream processing. Batch Operations are for bulk actions, not organization. Object Lock is for retention. S3 Select is for querying within files.

Answer

S3 Object Lock to prevent object modifications.

Answer

S3 Batch Operations to rename objects after upload.

Question 10

A company runs an Amazon RDS for PostgreSQL instance for an OLTP application. The database size is 500 GB. The company wants to minimize downtime during backups and ensure point-in-time recovery (PITR) for the last 7 days. Which TWO features should the company use? (Choose TWO.)

Accepted Answer

Enable Multi-AZ deployment for high availability.. Multi-AZ deployment for Amazon RDS provides high availability by automatically provisioning and maintaining a synchronous standby replica in a different Availability Zone. This minimizes downtime during backups by allowing automated backups to be taken from the standby instance, eliminating I/O suspension on the primary. Option C is correct because enabling automated backups with a retention period of 7 days enables point-in-time recovery (PITR) within that window, restoring the database to any second within the retention period using transaction logs.

Answer

Create a read replica in a different Availability Zone.

Answer

Create daily manual snapshots and copy them to another region.

Answer

Enable Enhanced Monitoring to track backup progress.

Question 11

A company uses AWS Glue to catalog data stored in Amazon S3. The data is in Parquet format and partitioned by date. The company wants to improve query performance in Amazon Athena and reduce costs. Which THREE actions should the company take? (Choose THREE.)

Accepted Answer

Partition the data by date so Athena can use partition pruning.. Partitioning the data by date allows Athena to use partition pruning, which limits the amount of data scanned by only reading the partitions that match the query's WHERE clause. This directly reduces both query cost (since Athena charges per byte scanned) and query latency, especially for date-range queries on large datasets.

Answer

Convert the data to JSON format for better schema evolution.

Answer

Use Glue DataBrew to clean the data before querying.

Question 12

A large e-commerce company uses Amazon DynamoDB to store shopping cart data. The table has a partition key of 'user_id' and a sort key of 'item_id'. The application performs frequent updates to the 'quantity' attribute for items in a user's cart. Recently, the operations team noticed that write requests are being throttled during peak shopping hours. The table is provisioned with 10,000 write capacity units (WCUs) and uses DynamoDB Accelerator (DAX) for read caching. The data engineer suspects that the throttling is due to hot partitions. The application uses a single AWS SDK client configured with retries. After reviewing the Amazon CloudWatch metrics, the engineer sees that the WriteThrottleEvents metric spikes for a few partition keys. The table has a high number of partitions. What should the data engineer do to resolve the throttling issue with minimal application changes?

Accepted Answer

Configure DynamoDB Auto Scaling with a maximum WCU setting of 20,000 and a target utilization of 70%.. DynamoDB Auto Scaling can dynamically adjust write capacity in response to traffic patterns, reducing throttling on hot partitions without requiring application changes. Option A is incorrect because permanently increasing WCUs does not adapt to variable demand and may lead to over-provisioning. Option B (Global Tables) replicates data across regions but does not increase write capacity for a single table, so it does not resolve hot partition throttling. Option C (DAX) is a read cache and does not offload write traffic; it only improves read performance.

Answer

Increase the provisioned write capacity to 20,000 WCUs permanently.

Answer

Enable DynamoDB Global Tables to distribute writes across regions.

Answer

Add more nodes to the DAX cluster to offload write traffic.

Question 13

A media company stores video files in Amazon S3 buckets organized by content type. The company has a requirement to automatically archive files that are older than 90 days to Amazon S3 Glacier Deep Archive to reduce costs. However, the company wants to retain the ability to restore files within 12 hours if needed. The data engineer creates an S3 Lifecycle policy to transition objects to Glacier Deep Archive after 90 days. After deploying the policy, the engineer notices that the storage costs have not decreased significantly. On reviewing the bucket metrics, the engineer sees that many objects are being deleted directly by users before the lifecycle policy takes effect. The company needs to enforce the lifecycle policy and prevent premature deletions. What should the data engineer do to enforce the lifecycle policy?

Accepted Answer

Enable S3 Versioning on the bucket and add a lifecycle rule to transition noncurrent versions to Glacier Deep Archive after 90 days.. Enabling S3 Versioning ensures that when users delete objects, a delete marker is created instead of permanently deleting the object. The lifecycle rule can then transition the noncurrent versions (the original objects) to Glacier Deep Archive after 90 days, preserving the data while reducing costs. Option A is incorrect because Object Lock with GOVERNANCE mode prevents any deletion or overwrite for the retention period, which may interfere with normal operations and does not address the lifecycle policy enforcement. Option C is incorrect because MFA Delete provides additional security for delete operations but does not prevent the deletion itself; it only requires MFA authentication. Option D is incorrect because S3 Glacier Select is used to query archived data, not for lifecycle management.

Answer

Apply an S3 Object Lock retention policy with a default retention mode of GOVERNANCE and a retention period of 90 days.

Answer

Enable S3 Multi-Factor Authentication (MFA) Delete on the bucket to require MFA for all delete operations.

Answer

Use S3 Glacier Select to query the objects and restore them if needed.

Question 14

A startup is building a real-time analytics application using Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics. The application processes clickstream data from a website. The data is also stored in Amazon S3 for historical analysis. The company uses an S3 bucket with a lifecycle policy that transitions objects to Amazon S3 Glacier Deep Archive after 30 days. The data engineering team has configured a Kinesis Data Firehose delivery stream to write data to the S3 bucket. The team notices that the data in S3 is not being transitioned to Glacier Deep Archive after 30 days. The lifecycle policy is correctly configured and has been verified. What is the most likely cause of this issue?

Accepted Answer

The S3 lifecycle rule is configured with a filter that does not match the prefix used by Kinesis Data Firehose.. The most likely cause is that the S3 lifecycle rule has a filter that does not match the prefix used by Kinesis Data Firehose. Firehose writes objects with a specific prefix pattern (e.g., 'year/month/day/hour/...'), and if the lifecycle rule is configured with a different prefix filter, the rule will not apply to those objects. Option A is correct. Option B is incorrect because the minimum 90-day storage period for Glacier Deep Archive is a billing consideration, not a restriction on lifecycle transitions; objects can be transitioned after 30 days, but early deletion fees may apply. Option C is incorrect because S3 Intelligent-Tiering is not required for lifecycle transitions to Glacier Deep Archive; any S3 bucket can have lifecycle rules. Option D is incorrect because S3 Batch Operations are not involved in lifecycle transitions; they are used for bulk operations like copying or restoring objects.

Answer

The Glacier Deep Archive storage class requires a minimum 90-day storage period, so the lifecycle policy cannot transition objects after 30 days.

Answer

The S3 bucket is not enabled for S3 Intelligent-Tiering, which is required for lifecycle transitions to Glacier Deep Archive.

Answer

The S3 bucket does not have S3 Batch Operations enabled to invoke the lifecycle policy.

Question 15

A healthcare company uses Amazon RDS for PostgreSQL to store patient records. The database has a size of 1 TB and is running on a db.r5.large instance. The company requires that the database be highly available and have automated backups with point-in-time recovery (PITR) for the last 35 days. The operations team has configured Multi-AZ deployment and automated backups with a 35-day retention period. During a recent disaster simulation, the team attempted to restore the database to a point in time from 30 days ago. The restore operation failed because the backup was not available. On investigation, the team found that the automated backups were being deleted before the retention period ended. The team also noticed that the database has a large number of transaction logs generating a high volume of write activity. What is the most likely cause of the backups being deleted prematurely?

Accepted Answer

The RDS instance was deleted, which automatically deletes all automated backups.. When an RDS instance is deleted, all automated backups associated with that instance are automatically deleted, regardless of the configured retention period. In this scenario, the instance was not explicitly described as deleted, but the deletion of automated backups before the retention period ends is a classic symptom of instance deletion. Option B is incorrect because a conflicting backup window does not cause backups to be deleted; it only affects when backups are taken. Option C is incorrect because Multi-AZ deployment does not affect backup retention; backups are still retained according to the retention period even if Multi-AZ is not enabled. Option D is incorrect because manual snapshots are independent of automated backups; deleting manual snapshots does not affect automated backup retention.

Answer

The automated backup window was set to a time that conflicted with the database maintenance window.

Answer

The Multi-AZ deployment was not enabled during the backup process, causing backups to fail.

Answer

The database had manual snapshots that were deleted manually by the operations team.