DEA-C01 Data Store Management Practice Test 13 — 15 Questions

Question 1

A company runs a production Amazon RDS for MySQL database with Multi-AZ deployment. The database experiences high read latency during peak hours. The company wants to improve read performance with minimal application changes. Which solution should a data engineer recommend?

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

Accepted Answer

Create one or more read replicas in a different Availability Zone.. Creating read replicas in a different Availability Zone offloads read traffic from the primary DB instance, reducing read latency during peak hours. Read replicas in Amazon RDS for MySQL are asynchronous replicas that can serve SELECT queries, requiring minimal application changes (only a new connection endpoint). This directly addresses high read latency without altering the existing Multi-AZ setup.

Answer

Use Amazon DynamoDB Accelerator (DAX) as a caching layer.

Answer

Increase the DB instance size to a larger instance class.

Answer

Enable Multi-AZ on the existing instance.

Question 2

Refer to the exhibit. A data engineer is troubleshooting an IAM policy attached to a user. The user reports that they cannot upload objects to the S3 bucket 'data-lake-bucket' unless they explicitly specify the 'x-amz-server-side-encryption' header with value 'AES256'. The engineer wants to modify the policy to allow uploads without requiring encryption headers, but still enforce encryption on the bucket itself. Which change should the engineer make?

Accepted Answer

Remove the entire Deny statement.. Removing the Deny statement eliminates the explicit denial that blocks uploads without the 'x-amz-server-side-encryption' header set to 'AES256'. The Allow statement already grants s3:PutObject, and by removing the Deny, users can upload without specifying encryption headers. The bucket's default encryption setting (e.g., AES256) will then automatically encrypt objects at rest, enforcing encryption without requiring the header in the request.

Answer

Remove the Condition block from the Allow statement.

Answer

Change the Condition in the Allow statement to use aws:kms instead of AES256.

Answer

Set the bucket's default encryption to AES256 and keep the policy unchanged.

Question 3

A company uses Amazon DynamoDB to store session data for a web application. The application experiences throttling errors during peak traffic. The data engineer observes that the table's read capacity is consistently at 100% and the write capacity is at 20%. The engineer needs to resolve the throttling with minimal cost. Which solution should the engineer implement?

Accepted Answer

Implement DynamoDB Accelerator (DAX) to cache read-heavy workloads.. The issue is read-heavy throttling with read capacity at 100% while write capacity is low. Implementing DynamoDB Accelerator (DAX) provides an in-memory cache that offloads read traffic from the table, reducing read capacity consumption and eliminating throttling without increasing provisioned capacity. This is the most cost-effective solution as it avoids scaling costs and leverages caching for repeated reads.

Answer

Increase the provisioned read capacity units for the table.

Answer

Enable DynamoDB auto scaling for read capacity.

Answer

Decrease the provisioned write capacity units to free up budget for reads.

Question 4

A data engineer needs to store log files from multiple applications in a central S3 bucket. The logs must be stored cost-effectively for long-term retention (7 years). The logs are accessed infrequently after the first 30 days. Which storage class should the engineer use for objects older than 30 days?

Accepted Answer

S3 Standard-IA. D is correct because S3 Standard-IA (Infrequent Access) is designed for data accessed less frequently but requires rapid access when needed, with a lower storage cost than S3 Standard and a 30-day minimum storage duration charge. After the first 30 days, logs are infrequently accessed, making Standard-IA the most cost-effective option that still provides millisecond first-byte latency for occasional retrieval needs over the 7-year retention period.

Answer

S3 Glacier Deep Archive

Answer

S3 Standard

Answer

S3 One Zone-IA

Question 5

A data engineer is designing a data store for a real-time analytics application that requires sub-millisecond read and write latency for time-series data. The data volume is expected to grow to hundreds of terabytes. Which TWO AWS services should the engineer consider? (Choose TWO.)

Accepted Answer

Amazon DynamoDB with Time-to-Live (TTL). Amazon DynamoDB with Time-to-Live (TTL) (B) is correct because DynamoDB is a fully managed, serverless NoSQL key-value store that delivers single-digit millisecond latency at any scale, and TTL automatically expires stale time-series items to control storage growth across hundreds of terabytes. Amazon Timestream (E) is correct because it is a purpose-built, serverless time-series database that provides fast ingestion and sub-millisecond-to-millisecond query latency for time-series workloads while automatically tiering data to cost-effective storage as volume grows. Amazon Redshift (A) is a petabyte-scale data warehouse optimized for analytical SQL queries, not sub-millisecond read/write latency. Amazon ElastiCache for Redis (C) offers sub-millisecond latency but is an in-memory cache, so it is not suited as the primary store for hundreds of terabytes of durable time-series data. Amazon RDS for PostgreSQL (D) is a relational database that cannot sustain sub-millisecond latency at that scale and requires manual sharding or partitioning for such volumes.

Answer

Amazon Redshift

Answer

Amazon ElastiCache for Redis

Answer

Amazon RDS for PostgreSQL

Question 6

A company has an S3 bucket with versioning enabled that stores critical data. The security team requires that once an object is deleted, it cannot be recovered by anyone, including the root user. Additionally, the company wants to ensure that objects cannot be overwritten for a specified period. Which THREE actions should the data engineer take to meet these requirements? (Choose THREE.)

Accepted Answer

Enable S3 Object Lock in compliance mode.. S3 Object Lock in compliance mode prevents objects from being deleted or overwritten by any user, including the root user, for the duration of the retention period. This meets the requirement that once an object is deleted, it cannot be recovered, because compliance mode locks are immutable and cannot be removed or shortened by anyone. Setting a retention period on the bucket using Object Lock ensures that objects cannot be overwritten for the specified period. Enabling S3 Versioning is necessary because Object Lock requires versioning to be enabled on the bucket to track object versions and enforce retention settings.

Answer

Enable MFA Delete on the bucket.

Answer

Configure a lifecycle policy to expire noncurrent versions after 1 day.

Question 7

A data engineer needs to migrate an on-premises MongoDB database to AWS. The migration must have minimal downtime and support automatic scaling. Which TWO AWS services should the engineer use for the target data store? (Choose TWO.)

Accepted Answer

Amazon DocumentDB (with MongoDB compatibility). Amazon DocumentDB (with MongoDB compatibility) is correct because it is a fully managed, MongoDB-compatible document database service that natively supports MongoDB workloads, allowing migration with minimal downtime using AWS Database Migration Service (DMS) and providing automatic storage scaling up to 64 TiB. Amazon DynamoDB is also correct because it is a fully managed NoSQL key-value and document database that offers seamless automatic scaling of throughput and storage via on-demand capacity mode, making it suitable as a target for a MongoDB migration when the schema can be adapted. Amazon Redshift is a petabyte-scale data warehouse for analytics, not a document store, so it does not fit the MongoDB migration scenario. Amazon RDS for MySQL is a relational database engine and cannot natively store MongoDB documents. Amazon S3 is object storage, not a database, so it cannot serve as the target data store for a MongoDB migration.

Answer

Amazon Redshift

Answer

Amazon RDS for MySQL

Answer

Amazon S3

Question 8

Refer to the exhibit. A data engineer is analyzing a query performance issue on an Amazon Redshift table. The table 'sales' has 100 million rows. The query is performing a full table scan. Which optimization should the engineer apply to improve query performance?

Accepted Answer

Use a compound sort key on (sale_date, region).. The query is performing a full table scan, which indicates that Redshift cannot efficiently prune blocks. A compound sort key on (sale_date, region) orders rows by sale_date first, then by region, allowing Redshift to skip large portions of data when filtering on the leading column (sale_date). This minimizes the number of blocks scanned and dramatically improves query performance for range-based or equality filters on the leading column.

Answer

Change DISTKEY to region.

Answer

Use an interleaved sort key on (sale_date, region).

Answer

Change DISTSTYLE to ALL.

Question 9

A financial services company has an Amazon DynamoDB table named 'Transactions' with provisioned read capacity of 10,000 RCU and write capacity of 5,000 WCU. The table stores transaction records for the past 90 days. The application performs point reads by transaction ID (partition key) and range queries by customer ID and timestamp (GSI). Recently, the company started a new marketing campaign, causing a sudden spike in write traffic. The write capacity is now at 4,500 WCU, and the application is experiencing occasional throttling on writes. The data engineer needs to ensure that writes are not throttled during future campaigns, while keeping costs low. The table currently has auto scaling enabled with a maximum capacity of 10,000 WCU. Which solution should the engineer implement?

Accepted Answer

Switch the table to DynamoDB on-demand capacity mode.. DynamoDB on-demand capacity mode automatically scales to accommodate traffic spikes, eliminating throttling without manual intervention and without fixed capacity limits, making it cost-effective for unpredictable traffic. Option B is wrong because DAX is a read cache and does not handle write throttling. Option C is wrong because using SQS adds latency and complexity; not ideal for real-time writes. Option D is wrong because increasing the maximum write capacity still has a limit and may not react quickly enough to sudden spikes, and may increase costs.

Answer

Use DynamoDB Accelerator (DAX) to cache write requests.

Answer

Implement an Amazon SQS queue to buffer write requests and process them in batches.

Answer

Increase the maximum write capacity in the auto scaling configuration to 20,000 WCU.

Question 10

A company runs an Amazon RDS for PostgreSQL database for its e-commerce platform. The application team reports that write-intensive workloads are causing high latency and the database is experiencing storage bottlenecks. The database currently uses General Purpose SSD (gp2) storage. Which action would be MOST effective in improving write performance without changing the database instance class?

Accepted Answer

Change the storage type to General Purpose SSD (gp3).. D is correct because gp3 storage provides a baseline performance that is higher than gp2 for the same storage size, and it allows you to independently provision IOPS and throughput without needing to increase storage. This directly addresses the write-intensive workload's high latency and storage bottleneck by offering up to 4,000 IOPS at no additional cost (compared to gp2's 3,000 IOPS baseline for larger volumes), and you can scale IOPS up to 16,000 without changing the instance class.

Answer

Create a read replica and offload writes to it.

Answer

Switch the storage type to Provisioned IOPS SSD (io1).

Answer

Enable Multi-AZ deployment for high availability.

Question 11

A data engineer is designing a data lake on Amazon S3 for a healthcare organization that must comply with HIPAA regulations. The data includes protected health information (PHI) and must be encrypted at rest. The organization requires that all encryption keys be managed by AWS and rotated automatically every year. Additionally, the data must be replicated to another AWS Region for disaster recovery. Which combination of S3 features should the engineer use to meet these requirements?

Accepted Answer

Use SSE-S3 with S3 Cross-Region Replication (CRR).. SSE-S3 provides server-side encryption with Amazon S3-managed keys, satisfying the requirement for AWS-managed keys with automatic annual rotation (SSE-S3 keys are rotated at least annually). S3 Cross-Region Replication (CRR) meets the disaster recovery requirement by automatically replicating objects to a different AWS Region. SSE-S3 encryption is applied at rest in both the source and destination buckets, and CRR works seamlessly with SSE-S3 without additional configuration for key management.

Answer

Use SSE-S3 with S3 Same-Region Replication (SRR).

Answer

Use SSE-KMS with S3 Cross-Region Replication (CRR).

Answer

Use SSE-C with S3 Cross-Region Replication (CRR).

Question 12

A data engineering team is using Amazon DynamoDB to store user session data for a web application. The application experiences sudden spikes in traffic, causing throttling on the DynamoDB table. The team wants to minimize throttling without over-provisioning read/write capacity. Which solution should the team implement?

Accepted Answer

Enable DynamoDB Accelerator (DAX) caching layer.. DynamoDB Accelerator (DAX) is a fully managed, in-memory cache that reduces read latency from single-digit milliseconds to microseconds. By caching frequently accessed items, DAX offloads read requests from the DynamoDB table, directly reducing the read capacity consumption and thus minimizing throttling during traffic spikes without requiring over-provisioning of read capacity units.

Answer

Enable DynamoDB Time to Live (TTL) to automatically delete expired items.

Answer

Disable auto scaling and manually set a high provisioned capacity.

Answer

Use Amazon RDS read replicas to offload read traffic.

Question 13

A company uses Amazon S3 to store large datasets for analytics. Each dataset is stored in a separate prefix and consists of thousands of small objects (1-10 KB each). The company notices that listing objects in a prefix takes several seconds, slowing down data processing. Which solution would MOST improve listing performance?

Accepted Answer

Use S3 Inventory to generate a daily listing of objects.. S3 Inventory provides a scheduled CSV/Parquet file listing all objects in a bucket or prefix, including metadata like size and last modified date. By querying this inventory file instead of issuing real-time ListObject API calls, you avoid the latency of enumerating thousands of small objects, dramatically improving listing performance for analytics workflows.

Answer

Add a lifecycle policy to transition objects to S3 Glacier.

Answer

Use S3 Select to filter objects during listing.

Answer

Increase the number of parallel requests by using more prefixes.

Question 14

A data engineer needs to store clickstream data from a web application in Amazon S3. Each event is about 5 KB, and the application generates 1 million events per hour. The data is used for real-time analytics and also for batch processing. The engineer wants to minimize storage costs while ensuring that data is available for real-time queries as soon as it is written. Which storage class should the engineer use for the S3 bucket?

Accepted Answer

S3 Standard.. S3 Standard is the correct choice because it offers low-latency (milliseconds) first-byte-out performance, making data available for real-time queries immediately after writing. It also supports both real-time analytics and batch processing without retrieval fees, and at 5 KB per event with 1 million events per hour (approximately 5 GB/hour or 120 GB/day), the storage cost is manageable compared to the frequent access pattern. S3 Standard is optimized for frequently accessed data and provides the durability and availability needed for clickstream analytics.

Answer

S3 Intelligent-Tiering.

Answer

S3 Standard-IA.

Answer

S3 Glacier Instant Retrieval.

Question 15

A company uses Amazon DynamoDB to store metadata for a document management system. The table has a partition key of document_id and a sort key of version. The application frequently queries for the latest version of a document by document_id. The data engineer notices that these queries are consuming a lot of read capacity. How can the engineer optimize the read performance and reduce read capacity consumption?

Accepted Answer

Create a global secondary index (GSI) and use DynamoDB Accelerator (DAX).. Creating a Global Secondary Index (GSI) with document_id as the partition key and version as the sort key, combined with DynamoDB Accelerator (DAX), allows the application to query the latest version efficiently. The GSI can be configured to project only the necessary attributes, reducing read capacity consumption, while DAX provides an in-memory cache that offloads repeated read requests from the DynamoDB table, significantly lowering read capacity units (RCUs) consumed.

Answer

Change the sort key to store version in descending order.

Answer

Enable DynamoDB Streams and use a read replica.

Answer

Decrease the ReadCapacityUnits of the table to force caching.