DEA-C01 Data Store Management Practice Test 12 — 15 Questions

Question 1

A data engineer needs to set up a new Amazon RDS for MySQL database for a web application. The application experiences variable read traffic and requires low read latency. The engineer needs to minimize downtime during maintenance and provide read scalability. Which configuration meets these requirements?

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

Accepted Answer

Multi-AZ db.r5.large instance with two Read Replicas. A Multi-AZ deployment provides high availability and automatic failover to minimize downtime during maintenance, while adding two Read Replicas offloads read traffic from the primary instance, reducing read latency and enabling read scalability. The db.r5.large instance size is sufficient for the variable read workload, and Read Replicas can be promoted to standalone instances if needed.

Answer

Multi-AZ db.r5.large instance

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Single-AZ db.r5.large instance

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Single-AZ db.r5.xlarge instance

Question 2

A data engineer is designing a data lake on Amazon S3. The data is partitioned by year, month, day, and hour. The engineer needs to ensure that queries using Amazon Athena are cost-effective and performant. The data is written in Parquet format, and the total volume is 50 TB. Which approach minimizes query costs?

Accepted Answer

Partition the data by year, month, day, and hour. Partitioning by year, month, day, and hour allows Athena to use partition pruning, reading only the relevant S3 prefixes instead of scanning the entire 50 TB dataset. This drastically reduces the amount of data scanned per query, which directly lowers query costs (Athena charges per TB scanned). The existing Parquet format further optimizes performance through columnar storage and compression.

Answer

Use AWS Glue Data Catalog to catalog the data

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Convert data to CSV format

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Use S3 Intelligent-Tiering storage class

Question 3

An e-commerce company uses Amazon DynamoDB as the primary data store for its product catalog. The table has a simple primary key (ProductID) and handles 10,000 writes per second during peak hours. Recently, the engineering team noticed increased write latency and throttled requests during peak times. The table's provisioned write capacity is set to 12,000 WCU. What is the most likely cause of the throttling?

Accepted Answer

Write traffic is unevenly distributed across partitions. DynamoDB partitions data by the primary key's hash value. If write traffic is unevenly distributed across partitions (e.g., a few ProductIDs receive most writes), those hot partitions can exceed their individual throughput limits (3,000 WCU per partition for provisioned tables), causing throttling even when the table's total provisioned WCU of 12,000 is not fully utilized.

Answer

The table has reached the maximum number of partitions

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DynamoDB Accelerator (DAX) is not configured

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A global secondary index is consuming write capacity

Question 4

A data engineer needs to store semi-structured JSON logs from multiple microservices in a cost-effective manner for later analysis using Amazon Athena. The logs are generated continuously, and the total volume is about 1 TB per day. The data must be queryable within minutes of arrival. Which storage solution is most appropriate?

Accepted Answer

Amazon S3 bucket with partitioned folders. Amazon S3 with partitioned folders is the most appropriate solution because it provides a cost-effective, scalable storage layer for semi-structured JSON logs, and integrates natively with Amazon Athena for serverless querying. By partitioning the data by time (e.g., year/month/day/hour), Athena can use partition pruning to minimize scanned data, enabling queries within minutes of arrival. S3's low cost per GB and lifecycle policies further optimize storage for the 1 TB/day volume.

Answer

Amazon DynamoDB table with JSON attribute

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Amazon RDS for PostgreSQL table with JSON column

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Amazon Redshift cluster with JSON ingestion

Question 5

A data engineer ran the command shown in the exhibit on the bucket 'my-data-lake'. The engineer then tries to delete an object version but receives an 'AccessDenied' error. The engineer has full S3 permissions via IAM. What is the most likely reason for the error?

Accepted Answer

MFA Delete is enabled, requiring multi-factor authentication. The command shown in the exhibit (likely `aws s3api put-bucket-versioning --bucket my-data-lake --versioning-configuration Status=Enabled,MFADelete=Enabled`) enables both versioning and MFA Delete on the bucket. When MFA Delete is enabled, any operation that permanently deletes an object version or changes the versioning state requires the request to include a multi-factor authentication token. Even though the engineer has full S3 permissions via IAM, the missing MFA token causes the 'AccessDenied' error. This is a bucket-level setting that overrides IAM permissions for these specific operations.

Answer

Versioning is suspended on the bucket

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The bucket policy denies s3:DeleteObjectVersion

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An S3 Object Lock retention policy is in effect

Question 6

A company is migrating its on-premises Oracle database to Amazon RDS for Oracle. The database is 2 TB in size and has a 24-hour maintenance window. The migration must have minimal downtime. Which AWS service should be used for the migration?

Accepted Answer

AWS Database Migration Service (DMS). AWS Database Migration Service (DMS) is the correct choice because it supports heterogeneous migrations (Oracle to RDS for Oracle) with minimal downtime using ongoing replication via Oracle LogMiner or binary reader. DMS can perform a full load of the 2 TB database and then continuously replicate changes from the source to the target during the 24-hour maintenance window, allowing a final cutover with only seconds of downtime.

Answer

Amazon RDS native backup and restore

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Amazon S3 Transfer Acceleration

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AWS Snowball Edge

Question 7

A data engineer created the IAM policy shown in the exhibit. The engineer then attempts to upload an object to 'my-bucket' using the AWS CLI with the command: aws s3 cp file.txt s3://my-bucket/ --sse aws:kms. The upload fails with an 'AccessDenied' error. What is the most likely cause?

Accepted Answer

The policy requires SSE-S3 (AES256), but the command uses SSE-KMS. The IAM policy in the exhibit requires the `s3:x-amz-server-side-encryption` header to be set to `AES256`, which corresponds to SSE-S3. The AWS CLI command uses `--sse aws:kms`, which sets the header to `aws:kms` for SSE-KMS. This mismatch causes the request to fail the `s3:PutObject` condition check in the policy, resulting in an 'AccessDenied' error.

Answer

The policy resource is incorrect

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The policy does not allow the s3:PutObject action

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The command is missing the --sse-customer-algorithm parameter

Question 8

A data engineer is configuring an Amazon S3 lifecycle policy to transition objects to S3 Glacier Deep Archive after 90 days. The bucket receives new objects daily. The engineer wants to ensure that objects are not deleted before 90 days. Which lifecycle action should be used?

Accepted Answer

Transition. (Transition) is correct because the S3 Lifecycle Transition action moves objects between storage classes over time. To ensure objects are moved to S3 Glacier Deep Archive after 90 days without deletion, a Transition rule is configured to specify the target storage class and the number of days from object creation.

Answer

Expiration

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NoncurrentVersionTransition

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AbortIncompleteMultipartUpload

Question 9

A financial services company is designing a data store for transaction records that must be immutable and auditable. The data must be stored for 7 years. Which AWS services can be combined to meet these requirements? (Choose TWO.)

Accepted Answer

Amazon S3 Glacier Deep Archive. Amazon S3 Glacier Deep Archive is correct because it provides the lowest-cost storage for long-term retention of immutable data, with a 7-year lifecycle meeting compliance requirements. Amazon S3 with Object Lock enabled is correct because it enforces a write-once-read-many (WORM) model, preventing records from being deleted or overwritten for a specified retention period, ensuring immutability and auditability.

Answer

Amazon EBS volume with snapshots

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Amazon RDS with automated backups

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Amazon DynamoDB with point-in-time recovery

Question 10

A data engineer is troubleshooting slow query performance on an Amazon Redshift cluster. The cluster has 10 nodes and is using automatic distribution style. The engineer suspects that data distribution is causing excessive data movement. Which steps should the engineer take to diagnose and resolve the issue? (Choose THREE.)

Accepted Answer

Choose appropriate distribution keys for large tables. Choosing appropriate distribution keys for large tables ensures that data is evenly distributed across the cluster slices, minimizing the need for data redistribution during joins and aggregations. Automatic distribution style may not always select the optimal key, leading to excessive data movement and slow query performance.

Answer

Run the VACUUM command to reclaim space

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Increase the number of nodes in the cluster

Question 11

A company uses Amazon DynamoDB for a gaming leaderboard. The table has a primary key of GameId (partition key) and Score (sort key). The application needs to retrieve the top 10 scores for a given game. Which strategies can improve query performance? (Choose TWO.)

Accepted Answer

Create a global secondary index with Score as sort key. Creating a global secondary index (GSI) with Score as the sort key allows efficient range queries on scores for a given GameId. DynamoDB can then use the GSI to retrieve the top 10 scores in sorted order without scanning the entire table, leveraging the index's sort key to fetch only the highest values.

Answer

Change the primary key to a single attribute

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Use a Scan operation with a limit

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Increase the write capacity units

Question 12

A data engineer is designing a data store for a real-time analytics application that requires sub-millisecond read and write latency. The data is accessed via a REST API. Which AWS services should the engineer consider? (Choose THREE.)

Accepted Answer

Amazon ElastiCache for Redis. Amazon ElastiCache for Redis is correct because it provides an in-memory data store that delivers sub-millisecond read and write latency, ideal for real-time analytics. Redis supports data structures like strings, hashes, and sorted sets, and can be accessed via REST API through a caching layer or directly with Redis commands. This makes it suitable for low-latency, high-throughput workloads where disk-based storage would introduce unacceptable delays.

Answer

Amazon S3

Answer

Amazon RDS for MySQL

Question 13

A data engineer reviewed the S3 lifecycle policy shown in the exhibit. The engineer notices that objects under the 'logs/' prefix are being deleted after 365 days. The business requirement is to retain logs for at least 5 years. What should the engineer change in the lifecycle policy?

Accepted Answer

Set the expiration days to 1825. The business requirement is to retain logs for at least 5 years, which is 1,825 days (5 × 365). The current lifecycle policy sets expiration to 365 days, causing premature deletion. By setting the expiration days to 1,825, the S3 lifecycle policy will delete objects under the 'logs/' prefix only after 5 years, meeting the retention requirement.

Answer

Change the prefix to 'logs/archive/'

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Change the transition to GLACIER on day 365

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Remove the expiration action

Question 14

A data engineer runs the describe-table command shown in the exhibit. The application frequently queries by CustomerID alone. Currently, these queries result in full table scans. Which action should the engineer take to improve query performance?

Accepted Answer

Create a global secondary index on CustomerID. The `describe-table` output shows CustomerID is the partition key, but the application frequently queries by CustomerID alone, which currently causes full table scans because there is no index supporting that query pattern. Creating a global secondary index (GSI) on CustomerID allows efficient querying by CustomerID without scanning the entire table, as the GSI provides a separate data structure with its own read/write capacity that can be queried directly.

Answer

Change the sort key to OrderID

Answer

Create a local secondary index on CustomerID

Answer

Increase the read capacity units to 500

Question 15

A data engineer is troubleshooting a slow Amazon Redshift query that joins several large tables. The query plan shows a large number of broadcasts. Which design change would most likely reduce the broadcast operations?

Accepted Answer

Change the DISTKEY on all tables to match the join column.. Setting the DISTKEY on all tables to the join column ensures that rows with the same join key value are co-located on the same compute node. This allows Redshift to perform a collocated join, eliminating the need to broadcast entire tables across the network, which is the primary cause of the slow query.

Answer

Change the SORT KEY on all tables to match the join column.

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Change the DISTSTYLE to EVEN on all tables.

Answer

Change the DISTSTYLE to ALL on all large tables.