DEA-C01 Data Store Management Practice Test 21 — 15 Questions

Question 1

A data engineering team is designing a data lake on Amazon S3. They need to store raw data in a format that supports schema evolution and is optimized for analytics with Amazon Athena. Which storage format should they use?

Accepted Answer

Parquet. Option B is correct because Parquet is a columnar format that supports schema evolution and is optimized for Athena. Option A (CSV) does not support schema evolution and is less efficient. Option C (Avro) is row-based and not as efficient for columnar queries. Option D (JSON) is text-based and not optimized.

Answer

CSV

Answer

Avro

Answer

JSON

Question 2

A company runs a MySQL database on Amazon RDS. The database size is 500 GB and is experiencing high read traffic. The team wants to improve read performance with minimal operational overhead. Which action should they take?

Accepted Answer

Create a read replica in the same region. Option A is correct because adding a read replica offloads read traffic from the primary with minimal overhead. Option B (multi-AZ) is for high availability, not read performance. Option C (larger instance) increases cost but does not specifically address read workload. Option D (ElastiCache) adds caching but requires application changes.

Answer

Enable Multi-AZ deployment

Answer

Implement Amazon ElastiCache for caching

Answer

Upgrade to a larger instance class

Question 3

A data engineer needs to transfer 10 TB of data from an on-premises Hadoop cluster to Amazon S3. The network bandwidth is limited to 100 Mbps, and the transfer must be completed within 48 hours. Which solution meets the requirements?

Accepted Answer

Use AWS Snowball Edge device to transfer data offline. Option D is correct because AWS Snowball Edge can transfer large data volumes offline within the time frame despite low bandwidth. Option A (S3 Transfer Acceleration) improves speed but not enough over 100 Mbps. Option B (Direct Connect) would require setup time. Option C (AWS DataSync) still depends on network bandwidth.

Answer

Use AWS DataSync to transfer data online

Answer

Use S3 Transfer Acceleration over the internet

Answer

Set up AWS Direct Connect to increase bandwidth

Question 4

A company has an Amazon DynamoDB table with on-demand capacity mode. The table stores session data for a web application. Recently, the application experienced throttling errors during a traffic spike. The team wants to prevent future throttling while optimizing costs. What should they do?

Accepted Answer

Implement a DynamoDB Accelerator (DAX) cluster. A DynamoDB Accelerator (DAX) cluster provides an in-memory cache that absorbs read-heavy traffic spikes, reducing the number of read requests that reach the underlying DynamoDB table. Since the throttling errors occurred during a traffic spike and the table uses on-demand capacity, which already scales automatically for writes and reads, the bottleneck is likely read-heavy traffic overwhelming the table's throughput. DAX offloads reads from the table, preventing throttling without requiring any changes to capacity mode, and it is cost-effective because it reduces read capacity unit consumption.

Answer

Enable DynamoDB auto scaling on the table

Answer

Switch to provisioned capacity with auto scaling

Answer

Increase the read and write capacity of the table

Question 5

A data engineer needs to store JSON documents that are frequently accessed by a low-latency web application. The data does not require complex queries, and the access pattern is primarily by a key. Which AWS service is most appropriate?

Accepted Answer

Amazon DynamoDB. Option A is correct because Amazon DynamoDB is a key-value and document database that offers low-latency access. Option B (RDS) is relational and not optimized for JSON. Option C (S3) has higher latency for frequent reads. Option D (ElastiCache) is a cache, not a primary store.

Answer

Amazon ElastiCache for Redis

Answer

Amazon S3

Answer

Amazon RDS for MySQL

Question 6

A company uses Amazon Redshift for data warehousing. The data team notices that queries are slow due to high disk usage on the cluster. They need to free up space without deleting any data. What should they do?

Accepted Answer

Run a deep copy to re-sort and reclaim space. Option B is correct because deep copy reorganizes data and reclaims disk space. Option A (VACUUM) reclaims space from deleted rows but does not reorganize. Option C (increasing node count) adds cost. Option D (changing sort keys) requires a table redesign.

Answer

Change the table's sort keys

Answer

Run VACUUM command

Answer

Add more nodes to the cluster

Question 7

A financial services company stores sensitive transaction data in an Amazon S3 bucket. Compliance requires that all objects be encrypted using SSE-KMS and that the bucket be protected from accidental deletion. Which combination of actions meets these requirements? (Select TWO.)

Accepted Answer

Add a bucket policy that denies PutObject if the object is not encrypted with SSE-KMS. Options A and C are correct because enabling versioning protects against accidental deletion and a bucket policy denying unencrypted uploads enforces SSE-KMS. Option B (default encryption) does not enforce encryption on existing objects. Option D (MFA delete) is an additional protection but not required by the scenario. Option E (block public access) addresses public access, not deletion.

Answer

Enable MFA Delete on the bucket

Answer

Enable S3 Block Public Access

Answer

Set default encryption to SSE-S3

Question 8

A startup is building a mobile application that requires a database to store user profiles and preferences. The database must scale automatically with minimal administration. Which AWS service should they use?

Accepted Answer

Amazon DynamoDB. Option B is correct because Amazon DynamoDB is a fully managed NoSQL database that scales automatically. Option A (RDS) requires manual scaling. Option C (Redshift) is for data warehousing. Option D (Aurora) is relational and requires some management.

Answer

Amazon Redshift

Answer

Amazon Aurora

Answer

Amazon RDS for PostgreSQL

Question 9

Which TWO actions can improve query performance on an Amazon Redshift cluster? (Choose two.)

Accepted Answer

Define appropriate sort keys. Options A and B are correct because sort keys improve data organization and compression reduces I/O. Option C (distribution style) affects data distribution but not directly query performance. Option D (increasing number of nodes) adds cost. Option E (vacuum) reclaims space but does not directly improve query speed.

Answer

Increase the number of nodes

Answer

Use EVEN distribution style for all tables

Answer

Run VACUUM command regularly

Question 10

Which THREE factors should a data engineer consider when choosing between Amazon S3 and Amazon DynamoDB for storing time-series data? (Choose three.)

Accepted Answer

Required query complexity (simple key lookups vs. range scans). Options B, C, and D are correct because data access patterns, query complexity, and latency requirements are key factors. Option A (cost) is a consideration but not specific to time-series. Option E (data volume) is less relevant as both scale.

Answer

Cost per GB of storage

Answer

Total data volume

Question 11

Which TWO features of Amazon S3 help protect data from accidental deletion or modification? (Choose two.)

Accepted Answer

S3 MFA Delete. Options A and B are correct because versioning allows recovery of previous versions and MFA delete adds an extra layer of protection. Option C (cross-region replication) is for disaster recovery, not accidental deletion. Option D (default encryption) protects data at rest, not deletion. Option E (lifecycle policies) automate transitions, not protection.

Answer

Lifecycle policies

Answer

Default encryption

Answer

Cross-Region Replication

Question 12

A company is using Amazon S3 to store large amounts of archival data. The data is accessed infrequently but must be immediately retrievable when needed. Which storage class is the most cost-effective choice?

Accepted Answer

S3 Standard-IA. S3 Standard-IA is designed for infrequently accessed data that requires rapid access. S3 Glacier Flexible Retrieval and S3 Glacier Deep Archive have retrieval delays. S3 Standard is more expensive for infrequent access.

Answer

S3 Standard

Answer

S3 Glacier Deep Archive

Answer

S3 Intelligent-Tiering

Question 13

A data engineer needs to set up a new Amazon RDS for PostgreSQL database for a production workload. The database must be highly available and resilient to a single Availability Zone failure. Which configuration should the engineer choose?

Accepted Answer

Multi-AZ deployment with one standby in a different AZ. Multi-AZ deployment with a standby in a different AZ provides high availability and automatic failover. Read replicas are for read scaling, not failover. Single-AZ lacks resilience.

Answer

Single-AZ with automated backups

Answer

Multi-AZ with two readable standbys

Answer

Single-AZ with a read replica

Question 14

A company wants to migrate its on-premises MySQL database to Amazon RDS for MySQL with minimal downtime. Which AWS service should be used for the migration?

Accepted Answer

AWS Database Migration Service (DMS). AWS Database Migration Service (DMS) supports continuous replication for minimal downtime. SCT helps with schema conversion but not migration. Direct Connect provides connectivity.

Answer

AWS Schema Conversion Tool (SCT)

Answer

AWS DataSync

Answer

AWS Direct Connect

Question 15

A data engineer is troubleshooting an Amazon DynamoDB table that has frequent throttling exceptions for write requests. The table has auto scaling enabled. What is the most likely cause?

Accepted Answer

The partition key is causing a hot partition. Hot partition is a common cause where a single partition key receives a disproportionate amount of writes, exhausting that partition's capacity. Auto scaling adjusts total capacity, not partition-level distribution.

Answer

The table's read capacity is set too low

Answer

The table's auto scaling is disabled

Answer

The table is using global tables without conflict resolution