DEA-C01 Mock Exam 89 — 25 Questions

Question 1

A data engineer is migrating an on-premises Oracle database to Amazon RDS for Oracle. The database is 5 TB in size and has a 1 Gbps network connection. The migration must be completed within 48 hours. Which service should be used?

Accepted Answer

AWS Database Migration Service (DMS).. AWS DMS is the correct choice because it is designed for migrating databases to AWS with minimal downtime, and it can handle a 5 TB Oracle database over a 1 Gbps network within 48 hours. DMS supports ongoing replication to keep the source and target in sync, and it can use Oracle-specific features like supplemental logging and change data capture (CDC) to reduce migration time. The 1 Gbps connection provides sufficient bandwidth to transfer 5 TB in under 12 hours at full utilization, leaving ample time for setup and validation.

Answer

AWS DataSync.

Answer

Amazon S3 Transfer Acceleration.

Answer

AWS Snowball Edge.

Question 2

A data engineer needs to store event data from IoT devices that arrives in bursts. The data is key-value and requires single-digit millisecond read and write latency. The engineer also needs to run complex analytical queries on the data for reporting. Which TWO services should be used together? (Choose TWO.)

Accepted Answer

Amazon DynamoDB. Amazon DynamoDB is correct because it provides single-digit millisecond read and write latency at any scale, making it ideal for IoT event data arriving in bursts. Its key-value data model matches the requirement, and it can serve as the operational data store for fast ingestion while supporting complex analytical queries when integrated with Amazon Redshift.

Answer

Amazon ElastiCache for Redis

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Amazon S3

Answer

Amazon RDS for MySQL

Question 3

A data engineer is designing a data store for real-time analytics on high-velocity clickstream data. The data must be stored in a schema-on-read format and support SQL queries with sub-second latency. Which service should be used?

Accepted Answer

Amazon Kinesis Data Firehose to S3 with Athena. Amazon Kinesis Data Firehose can ingest high-velocity clickstream data and deliver it to Amazon S3, where it is stored in a schema-on-read format (e.g., Parquet or ORC). Amazon Athena then allows SQL queries directly on the data in S3 with sub-second latency when using partitions, columnar formats, and optimizations like AWS Glue Catalog. This combination meets the requirements for real-time analytics without predefining a schema.

Answer

Amazon Redshift

Answer

Amazon Kinesis Data Analytics

Answer

Amazon DynamoDB

Question 4

A data engineer needs to store semi-structured JSON logs from multiple microservices in a cost-effective manner for ad-hoc querying using SQL. Which AWS service should be used?

Accepted Answer

Amazon Athena with data in S3. Amazon Athena is the correct choice because it allows you to query semi-structured JSON logs stored in S3 directly using standard SQL, without needing to load or transform the data. Athena's schema-on-read approach and pay-per-query pricing make it highly cost-effective for ad-hoc analysis of large volumes of log data, as you only pay for the data scanned during queries.

Answer

Amazon DynamoDB

Answer

Amazon RDS for MySQL

Answer

Amazon Kinesis Data Analytics

Question 5

Which THREE factors should be considered when choosing a partition key for an Amazon DynamoDB table?

Accepted Answer

If the table has a write-heavy workload, the partition key should distribute writes evenly.. Option B is correct because DynamoDB distributes data and request traffic across partitions based on the partition key. For write-heavy workloads, a partition key that evenly distributes writes prevents hot partitions, which can throttle requests and degrade performance. This ensures that no single partition exceeds its write capacity limit.

Answer

The partition key should be chosen to maximize the size of items in each partition.

Answer

The partition key should be chosen to minimize read capacity unit consumption.

Question 6

A company is using Amazon DynamoDB for a gaming application. They want to store player session data that expires after 24 hours. Which DynamoDB feature should be used?

Accepted Answer

Time to Live (TTL). Amazon DynamoDB Time to Live (TTL) allows you to define a per-item timestamp attribute that automatically deletes items after a specified duration. For the gaming session data that must expire after 24 hours, you can set the TTL attribute to the current time plus 24 hours, and DynamoDB will asynchronously delete expired items without any additional cost or write operations.

Answer

DynamoDB Streams

Answer

Global Tables

Answer

Point-in-Time Recovery

Question 7

Refer to the exhibit. An IAM policy is attached to a user. The user cannot upload objects to the S3 bucket 'example-bucket' using the AWS CLI. What is the most likely cause?

Accepted Answer

The user is not using HTTPS for API calls. The IAM policy explicitly denies all actions unless the request uses HTTPS (via the `aws:SecureTransport` condition key). Since the AWS CLI by default can use HTTP if not explicitly configured to use HTTPS, the user's upload attempt fails. The `s3:PutObject` action is allowed in the policy, but the condition block overrides that permission when the request is not made over HTTPS.

Answer

The policy does not allow s3:PutObject

Answer

The user is not in the same AWS region

Answer

The resource ARN does not include the bucket itself

Question 8

A healthcare company stores sensitive patient data in an S3 bucket (bucket name: patient-data-prod). The security team requires that all data be encrypted in transit and at rest, and that access be logged for auditing. The company currently uses S3 default encryption with SSE-S3. An external auditor finds that some objects have been uploaded without encryption because the default encryption setting was not applied to objects uploaded before the setting was enabled. The company wants to prevent any future unencrypted uploads and ensure all existing objects are encrypted. Which combination of actions should the data engineer take? (Choose TWO.)

Accepted Answer

Use S3 Batch Operations to copy all existing objects in place with the 'aws:Replicate' operation to apply default encryption.. To prevent unencrypted uploads, the bucket policy must deny PutObject requests that do not include the x-amz-server-side-encryption header with AES256. To encrypt existing objects, S3 Batch Operations can copy them in place with the default encryption setting applied. Option D alone only covers new objects, not existing ones. Option E is unnecessary because SSE-S3 uses AES256.

Answer

Enable S3 Object Ownership and set the bucket ACL to private.

Answer

Enable S3 default encryption on the bucket.

Answer

Create a bucket policy that denies s3:PutObject if the x-amz-server-side-encryption-aws-kms-key-id is not present.

Question 9

Refer to the exhibit. A data engineer is troubleshooting write throttling on the Orders table. The table has a composite primary key (OrderID as partition key, CustomerID as sort key). The engineer notices that writes are throttled even though the write capacity is not fully utilized. What is the most likely cause?

Accepted Answer

Writes are concentrated on a single partition key value.. D is correct because write throttling on an Amazon DynamoDB table occurs when requests exceed the provisioned throughput for a specific partition, even if the overall table write capacity is underutilized. With a composite primary key where OrderID is the partition key, writes concentrated on a single OrderID value (e.g., a hot key) will hit that partition's 3,000 WCU or 1,000 WCU (on-demand) limit, causing throttling while other partitions remain idle.

Answer

The table is empty and has no items.

Answer

A global secondary index (GSI) is consuming write capacity.

Answer

The read capacity units are too low.

Question 10

A company has a DynamoDB table with a partition key of 'user_id' and a sort key of 'timestamp'. They need to query all items for a user within a date range. Which query operation should be used?

Accepted Answer

Query with KeyConditionExpression on partition key and sort key. The Query operation in DynamoDB is designed to retrieve items based on a specific partition key and an optional sort key condition. Since the table has a partition key of 'user_id' and a sort key of 'timestamp', using Query with a KeyConditionExpression that filters on the partition key (user_id) and a range condition on the sort key (timestamp) is the most efficient and correct approach to get all items for a user within a date range.

Answer

BatchGetItem with multiple keys

Answer

GetItem with both partition and sort key

Answer

Scan with FilterExpression

Question 11

A company uses Amazon RDS for MySQL with Multi-AZ deployment. The primary instance fails, and automatic failover occurs. After failover, the data engineer notices that the new primary instance has a different DNS endpoint. Which TWO statements are true about this scenario? (Choose TWO.)

Accepted Answer

The DNS CNAME record is updated to point to the new primary.. Option C is correct because when Amazon RDS performs automatic failover in a Multi-AZ deployment, it updates the DNS CNAME record for the primary DB instance to point to the new primary (formerly the standby). This ensures that applications using the original endpoint are transparently redirected to the new primary without manual intervention.

Answer

The standby instance is created in the same Availability Zone as the failed primary.

Answer

A manual DNS update is required to connect to the new primary.

Answer

The endpoint changes to the standby instance's endpoint.

Question 12

A data engineer needs to store transaction data that requires strong consistency, ACID transactions, and complex join queries. Which AWS service is most appropriate?

Accepted Answer

Amazon RDS for PostgreSQL. Amazon RDS for PostgreSQL is the most appropriate choice because it provides full ACID transaction support, strong consistency, and the ability to perform complex join queries using standard SQL. Unlike NoSQL or data warehouse solutions, PostgreSQL is a relational database that excels at enforcing referential integrity and supporting multi-table joins with advanced indexing.

Answer

Amazon DynamoDB

Answer

Amazon S3

Answer

Amazon Redshift

Question 13

Which TWO statements are true about Amazon S3 bucket policies and ACLs?

Accepted Answer

ACLs are a legacy access control mechanism that is still supported.. Option B is correct because ACLs (Access Control Lists) are indeed a legacy access control mechanism that Amazon S3 continues to support for backward compatibility. While bucket policies and IAM policies are the modern, recommended approach, ACLs can still be used to grant basic read/write permissions to AWS accounts or predefined groups like AllUsers or AuthenticatedUsers.

Answer

When both exist, bucket policies are evaluated before ACLs.

Answer

ACLs can grant permissions to all authenticated AWS users.

Answer

ACLs support conditions such as IP address restrictions.

Question 14

A company is using Amazon S3 to store critical data and needs to ensure that objects are automatically transitioned to S3 Glacier Deep Archive after 180 days to reduce costs. Which S3 lifecycle action should be configured?

Accepted Answer

Transition. Option B is correct because the S3 lifecycle 'Transition' action is specifically designed to move objects between storage classes after a specified number of days. To reduce costs by moving objects to S3 Glacier Deep Archive after 180 days, you configure a lifecycle rule with a Transition action that targets the 'DEEP_ARCHIVE' storage class at the 180-day mark.

Answer

Expiration

Answer

AbortIncompleteMultipartUpload

Answer

NoncurrentVersionTransition

Question 15

A data engineer is migrating an on-premises Apache HBase workload to Amazon DynamoDB. The application requires strongly consistent reads and the ability to query by a composite key (partition key + sort key). Which DynamoDB table design should be used?

Accepted Answer

Create a table with a partition key and sort key, and use ConsistentRead parameter.. DynamoDB natively supports strongly consistent reads when you use the `ConsistentRead` parameter set to `true` on GetItem, Query, or Scan operations. By defining a table with a partition key and sort key, you can directly query by the composite key (partition key + sort key) with strong consistency, meeting both requirements without additional infrastructure.

Answer

Use a secondary index with strongly consistent reads.

Answer

Use a local secondary index (LSI) with the composite key.

Answer

Create a global secondary index (GSI) with the composite key.

Question 16

Which THREE considerations are important when designing a DynamoDB table for high-traffic gaming leaderboards? (Choose three.)

Accepted Answer

Enable DynamoDB Accelerator (DAX) for low-latency reads. DynamoDB Accelerator (DAX) provides in-memory caching for DynamoDB tables, reducing read latency from single-digit milliseconds to microseconds. For high-traffic gaming leaderboards, where millions of players query scores concurrently, DAX offloads read traffic from the main table, preventing throttling and ensuring consistent low-latency responses for the most frequently accessed data.

Answer

Use strongly consistent reads for all queries

Answer

Enable DynamoDB Streams for real-time updates

Question 17

A company is using Amazon DynamoDB for a high-traffic web application. They notice increased read latency during peak hours. Which design change would best reduce read latency without increasing cost?

Accepted Answer

Enable DynamoDB Accelerator (DAX). DynamoDB Accelerator (DAX) is an in-memory cache that reduces read latency from single-digit milliseconds to microseconds for eventually consistent reads, without requiring any changes to provisioned capacity. Since the question specifies reducing latency without increasing cost, DAX is ideal because it offloads read traffic from the underlying table, allowing you to potentially lower read capacity units (RCUs) while maintaining performance.

Answer

Increase read capacity units

Answer

Use DynamoDB global tables

Answer

Switch to strongly consistent reads

Question 18

Which TWO actions can help optimize Amazon S3 storage costs for a data lake? (Choose two.)

Accepted Answer

Use S3 Intelligent-Tiering for unpredictable access patterns. S3 Intelligent-Tiering automatically moves objects between two access tiers (frequent and infrequent) when access patterns change, with no retrieval fees and a small monthly monitoring fee. This is ideal for a data lake where access patterns are unpredictable, as it optimizes costs without requiring manual lifecycle rule adjustments.

Answer

Enable S3 Replication to another region

Answer

Use S3 Select to retrieve only needed data

Answer

Enable S3 Transfer Acceleration

Question 19

A company runs an Amazon RDS for PostgreSQL database. To meet disaster recovery requirements, they set up a cross-Region read replica. The replica has been lagging by several minutes. Which action is MOST effective to reduce the replica lag?

Accepted Answer

Increase the instance size (memory and CPU) of the replica.. Increasing the instance size (memory and CPU) of the cross-Region read replica is the most effective action because replica lag in Amazon RDS for PostgreSQL is often caused by the replica being unable to keep up with the volume of write-ahead log (WAL) data arriving from the primary. A larger replica instance provides more compute and memory resources to apply WAL changes faster, reducing the replay lag. This directly addresses the bottleneck at the replica side without impacting the primary database.

Answer

Enable Multi-AZ on the primary database.

Answer

Increase the instance size of the primary database.

Answer

Decrease the instance size of the replica to reduce cost.

Question 20

A data engineer is monitoring an Amazon EMR cluster running a Spark job. The job is processing a large dataset and the engineer notices that the cluster is using a high percentage of disk space on the core nodes. The job fails with 'No space left on device' error. What is the most effective way to resolve this issue without modifying the job logic?

Accepted Answer

Increase the number of core nodes in the cluster.. Option D is correct because increasing the number of core nodes distributes the intermediate shuffle data and temporary files across more nodes, reducing the per-node disk usage. This directly addresses the 'No space left on device' error without altering the Spark job logic, as core nodes in EMR store both HDFS data and local shuffle spills.

Answer

Attach additional EBS volumes to the core nodes.

Answer

Increase the EBS volume size attached to the core nodes.

Answer

Change the core node instance type to one with more memory.