DEA-C01 Multiple Select — 10 Questions

Question 1

A data engineer is designing a serverless data ingestion pipeline that uses Amazon Kinesis Data Firehose to deliver data to Amazon S3. The data must be transformed using AWS Lambda before being written to S3. Which two steps are required to enable this transformation? (Select TWO.)

Accepted Answer

Configure a Lambda function as a data transformation source in the Firehose delivery stream.. Option B is correct because Amazon Kinesis Data Firehose can be configured to invoke a Lambda function as a data transformation source. This allows Firehose to pass incoming records to the Lambda function, which processes and returns the transformed records before they are delivered to the S3 destination. Option C is correct because the Lambda function must return data in the specific format that Firehose expects, including a record ID, result status, and base64-encoded data, otherwise the transformation will fail.

Answer

Set up an S3 event notification to trigger the Lambda function on object creation.

Answer

Subscribe the Lambda function to the CloudWatch Logs log group for the Firehose stream.

Answer

Have the Lambda function write the transformed data directly to the S3 bucket.

Question 2

A company is building a data lake on Amazon S3. Data arrives from multiple sources in JSON, CSV, and Avro formats. The data must be transformed to Parquet and partitioned by date and source. Which TWO services can perform this transformation with minimal custom code? (Choose TWO.)

Accepted Answer

Amazon EMR with Spark. Amazon EMR with Spark is correct because Spark natively supports reading JSON, CSV, and Avro formats and writing Parquet with built-in partitioning by date and source. You can achieve this with a concise PySpark or Scala script that loads the data, applies partitioning logic, and writes to S3, requiring minimal custom code beyond the transformation logic.

Answer

AWS Lake Formation

Answer

Amazon Athena CTAS queries

Answer

Amazon Kinesis Data Firehose

Question 3

A data engineer is troubleshooting an AWS Glue job that reads from Amazon S3 and writes to Amazon Redshift. The job runs successfully but 5% of records are missing after the load. The engineer suspects data consistency issues. Which THREE actions could help diagnose and resolve the problem? (Choose THREE.)

Accepted Answer

Use the Redshift COPY command with a manifest file to load data.. Option A is correct because using the Redshift COPY command with a manifest file ensures that only the exact files listed in the manifest are loaded, eliminating the risk of partial or duplicate reads from S3. This is a common pattern to guarantee data consistency when the Glue job may not reliably track which files have been processed, especially in scenarios with concurrent writes or retries.

Answer

Increase the number of DPUs for the Glue job.

Answer

Use a staging table in Redshift with a transaction to commit.

Question 4

A company ingests IoT sensor data into Kinesis Data Streams. The data is then processed by a Lambda function that aggregates readings and writes to DynamoDB. The Lambda function is experiencing high error rates due to throttling. Which TWO actions would reduce throttling?

Accepted Answer

Increase the batch size in the Lambda event source mapping.. Option B is correct because increasing the batch size in the Lambda event source mapping allows each invocation to process more records from the Kinesis stream, reducing the number of concurrent Lambda invocations and thus lowering the risk of throttling. Option D is correct because switching DynamoDB to on-demand capacity mode eliminates write capacity limits, preventing throttling on the DynamoDB side that can cause Lambda retries and backpressure.

Answer

Increase the number of shards in the Kinesis stream.

Answer

Decrease the batch window in the Lambda event source mapping.

Answer

Increase the Lambda reserved concurrency to 1000.

Question 5

A company uses Amazon RDS for MySQL as a source for AWS DMS to replicate data to S3. The replication task is failing with 'OutOfMemory' errors on the DMS instance. The source table has 10 million rows with large BLOB columns. Which THREE changes would most likely resolve the issue?

Accepted Answer

Set the LOB column settings to 'Limited LOB mode' and specify a max LOB size.. Option A is correct because setting LOB columns to 'Limited LOB mode' with a specified max LOB size prevents DMS from loading entire LOBs into memory. Instead, DMS truncates LOBs to the specified size, reducing memory consumption and avoiding OutOfMemory errors when replicating large BLOB columns from MySQL to S3.

Answer

Disable logging for the DMS task to free memory.

Answer

Enable Full LOB mode to handle LOBs more efficiently.

Question 6

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 7

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 8

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 9

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 10

A data engineer is designing a data lake on Amazon S3 for analytics. The data includes sensitive PII that must be encrypted at rest. The company requires that the encryption keys be managed by the company's own hardware security module (HSM) and rotated every 90 days. Which TWO options meet these requirements? (Choose TWO.)

Accepted Answer

Use S3 server-side encryption with customer-provided keys (SSE-C). Option B is correct because SSE-C allows you to provide your own encryption keys, which can be managed and rotated from your own HSM. The keys are used server-side by S3 to encrypt objects at rest, but S3 does not store the keys—you manage them entirely, meeting the requirement for key management on your own HSM with 90-day rotation.

Answer

Use S3 server-side encryption with AWS KMS and an AWS managed key

Answer

Use client-side encryption with keys stored in AWS Secrets Manager

Answer

Use S3 server-side encryption with S3 managed keys (SSE-S3)