DEA-C01 Data Store Management — Timed 100 Questions

Question 1

A company has an Amazon RDS for MySQL DB instance with read replicas. The primary DB instance fails. What is the correct procedure to promote a read replica to become the new primary?

Accepted Answer

Manually promote the read replica to a standalone DB instance.. When an Amazon RDS for MySQL primary DB instance fails, read replicas do not automatically become the new primary. The correct procedure is to manually promote the read replica using the AWS Management Console, CLI, or API, which converts it into a standalone DB instance. After promotion, you must update your application endpoints to point to the new primary, as RDS does not handle this automatically.

Answer

Modify the read replica to be a Multi-AZ deployment and failover will occur.

Answer

RDS automatically fails over to the read replica within 5 minutes.

Answer

Delete the primary and the read replica will automatically become the primary.

Question 2

A data engineering team uses Amazon Redshift for analytics. They notice that queries on a large fact table are slow. The table is distributed using DISTSTYLE ALL. Which design change would most likely improve query performance?

Accepted Answer

Change DISTSTYLE to KEY on a column used in frequent joins.. DISTSTYLE ALL copies the entire table to every node, which is inefficient for large fact tables because it wastes storage and network bandwidth during data loading and query execution. Changing to DISTSTYLE KEY on a column used in frequent joins collocates related rows on the same slice, reducing the need to broadcast or redistribute data across the network during joins, which directly improves query performance.

Answer

Change DISTSTYLE to EVEN to distribute rows evenly across slices.

Answer

Increase the number of nodes in the Redshift cluster.

Answer

Change the table to use a SORTKEY on the most frequently filtered column.

Question 3

A company uses Amazon DynamoDB for a gaming application. They need to store player session data that expires after 24 hours. Which DynamoDB feature should they use to automatically delete expired items?

Accepted Answer

Time to Live (TTL). DynamoDB Time to Live (TTL) is the correct feature because it allows you to define a per-item timestamp attribute (e.g., `expireAt`) that DynamoDB automatically deletes once that timestamp is reached. This is ideal for expiring session data after 24 hours without requiring custom code or scheduled jobs to scan and delete items, reducing cost and operational overhead.

Answer

DynamoDB auto scaling

Answer

DynamoDB Streams

Answer

Point-in-time recovery

Question 4

Which TWO actions should a data engineer take to encrypt data at rest in an Amazon S3 bucket? (Select TWO.)

Accepted Answer

Configure the bucket to use SSE-KMS.. Option C is correct because SSE-KMS (Server-Side Encryption with AWS Key Management Service) encrypts data at rest in S3 by using a KMS key to manage encryption keys. This provides envelope encryption, where a CMK generates a data key that encrypts the object, and the data key is then encrypted by the CMK. Option D is correct because enabling default encryption on an S3 bucket using SSE-S3 (AES-256) ensures that all objects uploaded without explicit encryption headers are automatically encrypted at rest by S3's managed key.

Answer

Enable S3 Transfer Acceleration on the bucket.

Answer

Use client-side encryption before uploading objects to S3.

Answer

Attach a bucket policy that denies unencrypted PUT requests.

Question 5

A data engineer is designing a data lake on Amazon S3. The data must be immutable and support high-throughput streaming ingestion. Which THREE features should the engineer consider? (Select THREE.)

Accepted Answer

S3 Lifecycle policies to transition data to Amazon S3 Glacier. S3 Object Lock in governance mode (Option D) is correct because it enforces immutability by preventing objects from being deleted or overwritten for a specified retention period, which is essential for a data lake requiring immutable data. S3 Multipart Upload API (Option C) is correct because it enables high-throughput streaming ingestion by allowing large objects to be uploaded in parallel parts, improving throughput and resilience. S3 Lifecycle policies to transition data to Amazon S3 Glacier (Option B) is correct because it supports cost-effective storage management for immutable data that is rarely accessed, aligning with the data lake's lifecycle needs.

Answer

S3 Transfer Acceleration

Answer

S3 Cross-Region Replication (CRR)

Question 6

An e-commerce application uses Amazon ElastiCache for Redis to cache product catalog data. The cache currently uses lazy loading. The team wants to ensure that frequently accessed product data is always fresh. Which caching strategy should they implement?

Accepted Answer

Write-through caching. Write-through caching ensures that data is written to the cache simultaneously with the database, guaranteeing that frequently accessed product data is always fresh. This strategy eliminates stale reads by synchronously updating the cache on every write, which directly addresses the requirement for freshness without relying on expiration or lazy population.

Answer

Set a TTL of 5 minutes for all cached items

Answer

Use database read replicas to serve data

Answer

Lazy loading with TTL

Question 7

Refer to the exhibit. A data engineer has attached this bucket policy to an S3 bucket. What is the effect of this policy?

Accepted Answer

It allows the DataLakeRole to read and write objects, but only over HTTPS.. Option B is correct because the bucket policy uses a condition key `aws:SecureTransport` set to `true`, which restricts access to HTTPS (TLS) connections only. The `Principal` is `DataLakeRole`, and the `Action` includes `s3:GetObject` and `s3:PutObject`, so the policy allows that role to read and write objects exclusively over HTTPS, enforcing encrypted data in transit.

Answer

It enforces server-side encryption for all objects written to the bucket.

Answer

It allows anonymous access to the bucket for HTTPS requests.

Answer

It denies all access to the bucket except for requests from the DataLakeRole.

Question 8

Refer to the exhibit. A data engineer runs the above AWS CLI command to view the table metadata in the AWS Glue Data Catalog. The data is stored as CSV in S3 with partitions by year and month. When querying the table using Amazon Athena, no data is returned. What is the most likely cause?

Accepted Answer

The partitions have not been added to the Glue Data Catalog.. Option A is correct because the AWS CLI command shown only retrieves table metadata, not partition metadata. In AWS Glue, partitions must be explicitly added to the Data Catalog via `MSCK REPAIR TABLE`, `ALTER TABLE ADD PARTITION`, or a Glue crawler. Without partition metadata, Athena cannot locate the data files under the partitioned S3 paths (e.g., `s3://bucket/year=2024/month=01/`), resulting in zero rows returned even though the table schema is defined.

Answer

The SerDe is not compatible with CSV files.

Answer

The S3 location points to a file instead of a folder.

Answer

The column data types are incorrect for the CSV data.

Question 9

Which THREE storage classes in Amazon S3 are designed for infrequently accessed data with millisecond retrieval times? (Select THREE.)

Accepted Answer

S3 One Zone-IA. S3 One Zone-IA is designed for infrequently accessed data that requires millisecond retrieval times, but does not require the resilience of multiple Availability Zones. It stores data in a single AZ and offers the same low-latency performance as S3 Standard, making it suitable for non-critical, infrequently accessed data.

Answer

S3 Glacier Flexible Retrieval

Answer

S3 Glacier Deep Archive

Question 10

A company stores time-series sensor data in Amazon S3. They need to query the data using SQL with minimal latency and no infrastructure management. Which service should they use?

Accepted Answer

Amazon Athena. Amazon Athena is the correct choice because it is a serverless interactive query service that allows you to analyze data directly in Amazon S3 using standard SQL without any infrastructure to manage. It is optimized for querying structured, semi-structured, and unstructured data stored in S3, making it ideal for time-series sensor data with minimal latency requirements.

Answer

Amazon Kinesis Data Analytics

Answer

Amazon Redshift

Answer

Amazon DynamoDB

Question 11

A data engineer needs to migrate an on-premises MySQL database to Amazon RDS for MySQL with minimal downtime. Which approach should they use?

Accepted Answer

Use AWS Database Migration Service (DMS) with ongoing replication from the source database.. AWS DMS with ongoing replication (change data capture, CDC) is the correct approach because it allows continuous synchronization from the on-premises MySQL source to the RDS target, enabling a cutover with minimal downtime. Unlike one-time export/import tools, DMS captures ongoing changes during the migration, so the target stays up-to-date until you switch over.

Answer

Use mysqldump to export the database and import into RDS.

Answer

Create an RDS read replica and promote it.

Answer

Use AWS Schema Conversion Tool (SCT) to convert the schema and then copy data.

Question 12

A company uses Amazon DynamoDB with on-demand capacity. They notice higher than expected costs due to a sudden spike in read traffic from a reporting job. The reporting job scans the entire table daily. What is the most cost-effective way to reduce costs while maintaining the same reporting output?

Accepted Answer

Use a Global Secondary Index (GSI) with a sort key that matches the reporting query pattern.. Option B is correct because using a Global Secondary Index (GSI) with a sort key tailored to the reporting query pattern allows the reporting job to query only the relevant items instead of scanning the entire table. This reduces the read capacity units consumed per operation, directly lowering costs under on-demand capacity, which charges per RCU consumed. The reporting output remains identical because the GSI returns the same data filtered by the query pattern.

Answer

Enable DynamoDB Accelerator (DAX) for caching.

Answer

Set a TTL attribute to automatically expire old data.

Answer

Reduce the read capacity units (RCU) in the table.

Question 13

A data engineer has set up an Amazon S3 lifecycle policy to transition objects to Glacier Instant Retrieval after 30 days. After 60 days, objects should transition to Deep Archive. However, objects are not transitioning to Deep Archive. What is the most likely cause?

Accepted Answer

The transition to Deep Archive requires a minimum of 30 days after the previous transition.. Amazon S3 lifecycle policies require a minimum of 30 days between successive transitions when moving objects from one storage class to another. Since the policy transitions objects to Glacier Instant Retrieval after 30 days, the subsequent transition to Deep Archive cannot occur until at least 60 days after creation (30 days for the first transition plus 30 days minimum gap). The current policy attempts the Deep Archive transition at 60 days, which is exactly 30 days after the first transition, meeting the minimum requirement. However, the most likely cause of the failure is that the policy is incorrectly configured or the objects are too new; given the options, the correct answer is that the transition to Deep Archive requires a minimum of 30 days after the previous transition, and the policy as described should work if the objects are older than 60 days, but the question implies a timing issue.

Answer

The bucket has versioning enabled.

Answer

Deep Archive is not supported in the bucket's region.

Answer

Objects are smaller than 128 KB.

Question 14

A data engineer attaches the above IAM policy to an IAM user. The user tries to download an object from my-bucket using the AWS CLI without specifying SSE headers. The object is stored with SSE-S3. Will the download succeed?

Accepted Answer

No, because the request does not include the required encryption header.. Option B is correct because when an object is stored with SSE-S3, AWS S3 requires that any request to download it without specifying the `x-amz-server-side-encryption` header (or the equivalent CLI parameter) will fail. The IAM policy grants `s3:GetObject` but does not override the S3 API's requirement for the encryption header to be present in the request. Without the header, S3 rejects the request with a `400 Bad Request` error, even though the user has the necessary IAM permissions.

Answer

No, because the object is encrypted and the user does not have decrypt permission.

Answer

Yes, because the object is encrypted with SSE-S3, which uses AES256.

Answer

Yes, because the policy allows s3:GetObject on the bucket.

Question 15

A company is designing a data lake on Amazon S3. Which TWO strategies improve query performance for Amazon Athena?

Accepted Answer

Partition the data by frequently queried columns such as date or region.. Partitioning data by frequently queried columns (e.g., date or region) allows Athena to prune the data scanned by only reading the relevant partitions, reducing the amount of data scanned and improving query performance. This is a core optimization for Athena, which charges based on data scanned and performs better with less I/O.

Answer

Enable S3 Versioning on the bucket.

Answer

Use server-side encryption with AWS KMS (SSE-KMS).

Answer

Store data in CSV format with header rows.

Question 16

A company is migrating a legacy data warehouse to Amazon Redshift. They need to choose a distribution style to minimize data movement during joins. Which THREE factors should they consider?

Accepted Answer

The size of the table (number of rows).. Option A is correct because the size of the table (number of rows) directly influences the distribution strategy. In Amazon Redshift, large tables benefit from a distribution style that evenly distributes rows across slices to avoid data skew, which can cause performance bottlenecks during joins. Choosing a distribution key that aligns with the join columns minimizes data movement, but the table size determines whether an ALL distribution (for small tables) or a KEY distribution (for large tables) is more appropriate to reduce shuffling.

Answer

The number of columns in the table.

Answer

The data type of the distribution key column.

Question 17

A company runs a multi-AZ Amazon RDS for PostgreSQL instance. They need to run a one-time analytical query that will take several hours and consume significant I/O. The query should not impact the primary workload. What should the data engineer do?

Accepted Answer

Create a read replica of the RDS instance and run the query on the replica.. Option A is correct because creating a read replica of the RDS for PostgreSQL instance allows the analytical query to run on a separate database engine without affecting the primary workload. Read replicas in Amazon RDS use asynchronous replication from the source instance, so the replica can handle heavy I/O and long-running queries independently. This ensures the primary instance remains available for the production workload without performance degradation.

Answer

Run the query directly on the primary instance during off-peak hours.

Answer

Increase the instance size to handle the load.

Answer

Enable Multi-AZ and run the query on the standby instance.

Question 18

A company is migrating its on-premises MySQL database to Amazon RDS for MySQL. They want to minimize downtime and ensure data consistency. 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 is specifically designed for migrating databases to AWS with minimal downtime. DMS supports homogeneous migrations like MySQL to Amazon RDS for MySQL, and it uses ongoing replication (change data capture) to keep the source and target databases in sync during the migration, ensuring data consistency and allowing a cutover with only seconds of downtime.

Answer

AWS S3 Transfer Acceleration

Answer

AWS Glue

Answer

AWS Snowball Edge

Question 19

A data engineer is troubleshooting a slow-running query on an Amazon Redshift cluster. The query involves joining two large tables. The engineer notices that the query plan shows a large number of distribution and broadcast operations. Which design change would most likely improve query performance?

Accepted Answer

Change the distribution style of both tables to KEY on the join column. Option B is correct because changing the distribution style of both tables to KEY on the join column ensures that rows with the same join key value are co-located on the same node. This eliminates the need for expensive broadcast or redistribution operations during the join, as Redshift can perform the join locally on each slice without moving data across the network.

Answer

Change the distribution style of both tables to ALL

Answer

Change the distribution style of both tables to EVEN

Answer

Add a sort key on the join column

Question 20

A company uses Amazon DynamoDB for a gaming leaderboard. The table has a partition key of 'game_id' and a sort key of 'score'. The read capacity is provisioned at 1000 RCUs. During peak hours, users report high latency when querying the top 10 scores for a specific game. The DynamoDB metrics show ConsumedReadCapacityUnits averaging 800 but occasional throttling. What is the most likely cause and solution?

Accepted Answer

The hot game_id partition is exceeding its throughput; add DynamoDB Accelerator (DAX) to cache reads. The hot game_id partition is exceeding its provisioned throughput because DynamoDB distributes RCUs evenly across partitions, and a single partition can only handle up to (1000 RCUs / number of partitions) per second. When a specific game_id becomes popular, all reads hit the same partition, causing throttling despite low overall consumed capacity. Adding DynamoDB Accelerator (DAX) caches the top 10 scores for that partition, reducing read pressure and eliminating throttling without increasing RCUs.

Answer

Create a global secondary index with the same key schema to distribute reads

Answer

Remove the sort key and use a global secondary index

Answer

Increase the provisioned RCUs to 2000