DEA-C01 Data Store Management Practice Test 7 — 15 Questions

Question 1

A data engineer is troubleshooting an Amazon RDS for MySQL instance that is experiencing high read latency. The instance is a Single-AZ db.r5.large with 100 GB of General Purpose (gp2) storage. Which action is most likely to reduce read latency?

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

Accepted Answer

Create a read replica and direct read queries to it.. Creating a read replica offloads SELECT queries from the primary instance, directly reducing the read load and thus read latency. Since the instance is Single-AZ and experiencing high read latency, a read replica distributes the read traffic without altering the existing storage or availability configuration.

Answer

Enable automatic backups with a 7-day retention.

Answer

Increase the allocated storage to 200 GB.

Answer

Convert the instance to a Multi-AZ deployment.

Question 2

A company is building a real-time analytics dashboard using Amazon Kinesis Data Streams and Amazon DynamoDB. The data engineer needs to ensure that the DynamoDB table can handle write spikes without throttling. Which approach is the most cost-effective?

Accepted Answer

Use DynamoDB on-demand capacity mode.. DynamoDB on-demand capacity mode automatically scales to handle write spikes without requiring capacity planning or management, making it the most cost-effective choice for unpredictable workloads like a real-time analytics dashboard. It charges per request, so you only pay for the writes you actually use, avoiding over-provisioning costs.

Answer

Use DynamoDB Accelerator (DAX) to cache writes.

Answer

Use provisioned capacity with auto-scaling set to a maximum of 10,000 WCU.

Answer

Use an Amazon Lambda function to buffer writes and batch them to DynamoDB.

Question 3

Which TWO actions are recommended for securing data at rest in Amazon S3? (Choose two.)

Accepted Answer

Enable default encryption on the S3 bucket using SSE-S3 or SSE-KMS.. Enabling default encryption on an S3 bucket using SSE-S3 or SSE-KMS ensures that all objects stored in the bucket are encrypted at rest automatically, even if the upload request does not include encryption headers. This satisfies the requirement for securing data at rest by applying server-side encryption to every object written to the bucket.

Answer

Use S3 Bucket Key to reduce KMS request costs.

Answer

Enable S3 Versioning to protect against accidental deletions.

Answer

Configure cross-region replication to replicate data to another bucket.

Question 4

Which THREE factors should a data engineer consider when choosing between Amazon Redshift and Amazon Athena for querying large datasets in Amazon S3? (Choose three.)

Accepted Answer

Redshift requires provisioning and managing clusters, while Athena is serverless.. Amazon Redshift requires manual provisioning, configuration, and ongoing management of clusters, including node sizing, scaling, and maintenance windows. In contrast, Amazon Athena is a serverless service that automatically handles infrastructure, requiring no cluster management and allowing users to query data directly from Amazon S3 without any setup overhead.

Answer

Both support standard SQL queries.

Answer

Athena can only query data stored in Amazon S3, while Redshift can also query data in S3.

Question 5

Which TWO features of Amazon DynamoDB help ensure high availability and durability? (Choose two.)

Accepted Answer

Data is automatically replicated across multiple Availability Zones within an AWS Region.. DynamoDB automatically replicates data synchronously across three Availability Zones (AZs) within an AWS Region. This built-in replication ensures that even if an entire AZ fails, the data remains available and durable, providing a 99.999999999% (11 nines) durability SLA.

Answer

Auto-scaling adjusts provisioned capacity based on traffic.

Answer

Global tables enable active-active replication across multiple AWS Regions.

Answer

Time to Live (TTL) automatically deletes expired items.

Question 6

A company stores sensitive user data in an Amazon RDS for PostgreSQL DB instance. A security audit requires that all data be encrypted at rest. The database is currently unencrypted. What is the MOST operationally efficient way to enable encryption at rest?

Accepted Answer

Take a snapshot of the DB instance, copy it with encryption enabled, and restore the snapshot to a new DB instance.. RDS for PostgreSQL does not support enabling encryption at rest on an existing unencrypted DB instance directly. The only way to achieve this is by taking a snapshot of the unencrypted instance, creating an encrypted copy of that snapshot, and then restoring it to a new encrypted DB instance. This method is operationally efficient as it uses native RDS snapshot copy and restore capabilities without requiring additional infrastructure or manual data migration.

Answer

Create a read replica with encryption enabled and promote it.

Answer

Modify the DB instance and enable encryption in the console.

Answer

Modify the DB parameter group to include encryption parameters and reboot the instance.

Question 7

A data engineer is designing a data lake on Amazon S3 for storing raw sensor data. The data is append-only and accessed infrequently after 30 days. Compliance requires that data be retained for 7 years. Which S3 storage class is the MOST cost-effective for data older than 30 days?

Accepted Answer

S3 Glacier Deep Archive. B is correct because Amazon S3 Glacier Deep Archive is the most cost-effective storage class for data that is accessed infrequently and must be retained for long periods (7 years). For data older than 30 days, the retrieval time of 12 hours is acceptable given the append-only, infrequent access pattern, and the storage cost is significantly lower than other classes.

Answer

S3 Standard-IA

Answer

S3 One Zone-IA

Answer

S3 Intelligent-Tiering

Question 8

A company uses Amazon EMR to process large datasets stored in Amazon S3. The cluster uses a transient configuration and stores intermediate data on HDFS. After a job fails due to a spot instance termination, the data engineer needs to rerun the job. What should the engineer do to minimize data loss and cost?

Accepted Answer

Configure the cluster with a mix of spot and on-demand instances and set HDFS replication to 3.. Using a mix of spot and on-demand instances balances cost savings with fault tolerance, while setting HDFS replication to 3 ensures that intermediate data on HDFS survives the loss of a single node (e.g., a terminated spot instance). This allows the job to resume from the last checkpoint or reduce recomputation, minimizing both data loss and cost.

Answer

Use a long-running cluster with all on-demand instances to avoid interruptions.

Answer

Configure the cluster to use EMRFS and store intermediate data in S3.

Answer

Increase the HDFS replication factor to 5 and use only spot instances.

Question 9

A data engineer is migrating an on-premises Apache Cassandra cluster to Amazon Keyspaces (for Apache Cassandra). The cluster has 10 TB of data. The migration must minimize application downtime. Which strategy should the engineer use?

Accepted Answer

Set up a dual-write pattern where the application writes to both the on-premises cluster and Keyspaces, then switch reads to Keyspaces once data is synchronized.. The dual-write pattern allows the application to write to both the on-premises Cassandra cluster and Amazon Keyspaces simultaneously, ensuring data consistency with minimal downtime. Once the existing data is backfilled and the systems are synchronized, reads can be switched to Keyspaces with near-zero application interruption. This approach avoids the downtime required for bulk export/import or snapshot restore.

Answer

Export the data using the Cassandra COPY command and import it into Keyspaces using the COPY command.

Answer

Take a snapshot of the on-premises cluster and restore it to Keyspaces using the Keyspaces console.

Answer

Use AWS Database Migration Service (DMS) to continuously replicate data from the on-premises cluster to Keyspaces.

Question 10

A company uses Amazon DynamoDB to store session data for a web application. The application experiences sudden spikes in traffic, causing occasional throttling errors. The data engineer needs to handle these spikes without over-provisioning capacity. What is the MOST cost-effective solution?

Accepted Answer

Configure DynamoDB Auto Scaling to automatically adjust provisioned capacity.. DynamoDB Auto Scaling (option C) is the most cost-effective solution because it automatically adjusts the provisioned read/write capacity based on actual traffic patterns, handling sudden spikes without manual intervention or over-provisioning. This avoids paying for unused capacity during low-traffic periods while still accommodating bursts within the configured limits.

Answer

Set up a TTL (Time to Live) attribute to automatically delete old session data.

Answer

Enable DynamoDB Accelerator (DAX) to cache read requests.

Answer

Switch to DynamoDB on-demand mode.

Question 11

A data engineer is designing a data warehouse using Amazon Redshift. The workload includes complex queries that join large tables. The engineer notices that queries are slow due to disk-based operations. Which configuration change would MOST improve query performance?

Accepted Answer

Choose an appropriate distribution style (e.g., KEY or ALL) for the tables.. Choosing an appropriate distribution style (KEY or ALL) minimizes data movement between nodes during query execution. In Amazon Redshift, disk-based operations often result from large volumes of data being redistributed across the network for joins. By colocating related data on the same slices via KEY distribution or replicating small tables with ALL distribution, you reduce the need for broadcast or redistribution, which directly alleviates disk-based spills and improves query performance.

Answer

Define appropriate sort keys on the large tables.

Answer

Increase the number of slices per node by choosing a different node type.

Answer

Enable compression on all columns.

Question 12

A company uses Amazon S3 to store historical financial records. A compliance policy requires that all objects be encrypted with a customer-managed key stored in AWS KMS. The bucket is already configured with SSE-S3. What is the LEAST disruptive way to change the encryption to SSE-KMS?

Accepted Answer

Copy all objects to a new bucket that has default encryption set to SSE-KMS.. Changing the default encryption settings of an existing bucket (SSE-S3 to SSE-KMS) does not retroactively encrypt objects that were already stored with SSE-S3. Copying all objects to a new bucket that has default encryption set to SSE-KMS ensures every object is encrypted with a customer-managed key, as the copy operation re-encrypts each object using the new bucket's default settings. This approach is the least disruptive because it avoids modifying the original bucket's configuration or policies, which could break existing applications or access patterns.

Answer

Add a bucket policy to enforce SSE-KMS.

Answer

Update the bucket's default encryption settings to SSE-KMS.

Answer

Use S3 Batch Operations to apply SSE-KMS to all existing objects.

Question 13

A data engineer needs to store JSON documents that are accessed by a serverless application using AWS Lambda. The documents are frequently updated and need low latency (single-digit milliseconds) for read and write operations. Which AWS service should the engineer use?

Accepted Answer

Amazon DynamoDB. Amazon DynamoDB is a fully managed NoSQL key-value and document database that provides single-digit millisecond latency for read and write operations at any scale. It natively supports JSON documents, integrates directly with AWS Lambda via the AWS SDK, and handles frequent updates efficiently through its auto-scaling and on-demand capacity modes, making it ideal for serverless applications requiring low-latency data access.

Answer

Amazon ElastiCache for Redis

Answer

Amazon S3 (with S3 Select)

Answer

Amazon RDS for MySQL

Question 14

A company runs a critical application on Amazon RDS for MySQL that requires a Recovery Point Objective (RPO) of 5 minutes and a Recovery Time Objective (RTO) of 1 hour. The database is 500 GB. What is the MOST cost-effective disaster recovery solution that meets these requirements?

Accepted Answer

Use a Multi-AZ deployment with automatic failover.. Multi-AZ RDS for MySQL provides synchronous standby replication to a second Availability Zone, enabling automatic failover with minimal data loss (typically zero) and RTO under 1 hour. This meets the RPO of 5 minutes and RTO of 1 hour without manual intervention, and is more cost-effective than a cross-region replica for a 500 GB database.

Answer

Deploy the database in a single Availability Zone and perform manual point-in-time restores.

Answer

Take automated snapshots daily and store them in Amazon S3.

Answer

Create a cross-region read replica and promote it during a disaster.

Question 15

A data engineer is designing a data storage solution for IoT sensor data that is ingested at high velocity. The data is time-series and needs to be queried by time range. Which TWO AWS services are suitable for this use case? (Choose TWO)

Accepted Answer

Amazon Timestream. Amazon Timestream is a purpose-built time-series database that automatically scales to handle high-velocity IoT sensor data, with built-in time-based partitioning and query optimization for time-range queries. It supports SQL-like queries with time-series functions (e.g., `BETWEEN`, `DATE_BIN`) and separates storage into a memory store for recent data and a magnetic store for historical data, enabling efficient querying by time range.

Answer

Amazon RDS

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Amazon Redshift

Answer

Amazon S3