DEA-C01 Practice Test 2 — 10 Questions

Question 1

A company is using AWS Glue to run ETL jobs that write data to an Amazon S3 data lake. The jobs are failing with '503 Slow Down' errors. The data engineering team has already implemented retries. What is the BEST long-term solution?

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

Accepted Answer

Implement a backoff strategy to reduce the request rate.. The '503 Slow Down' error from Amazon S3 indicates that the request rate is too high and S3 is throttling the requests. The best long-term solution is to implement a backoff strategy (exponential backoff) to reduce the request rate, which allows the Glue job to automatically slow down and retry with increasing delays, aligning with S3's request rate limits and avoiding sustained throttling.

Answer

Enable S3 Transfer Acceleration.

Answer

Use S3 multipart upload for all objects.

Answer

Increase the number of retries in the Glue job.

Question 2

A data engineer is evaluating storage options for a new application that requires low-latency access to unstructured blobs (up to 5 TB each) with high throughput. The data will be accessed frequently for the first 30 days and then rarely. Which TWO storage solutions meet these requirements? (Choose TWO)

Accepted Answer

Amazon S3 with lifecycle policies. Amazon S3 with lifecycle policies is correct because S3 provides low-latency access to unstructured blobs (up to 5 TB each) with high throughput, and lifecycle policies can automatically transition objects to colder storage tiers (e.g., S3 Glacier Deep Archive) after 30 days, matching the access pattern of frequent then rare access.

Answer

Amazon EBS with io2 Block Express volumes

Answer

Amazon EFS

Answer

Amazon RDS for PostgreSQL

Question 3

A company uses Amazon S3 as a data lake. A data engineer needs to ensure that all objects uploaded to the 'incoming' prefix are automatically encrypted at rest using AWS KMS with a specific customer managed key. What is the simplest way to enforce this?

Accepted Answer

Use a bucket policy that denies PutObject requests without the required encryption header.. A bucket policy with a condition that denies PutObject requests unless the request includes the required encryption headers (x-amz-server-side-encryption: aws:kms and x-amz-server-side-encryption-aws-kms-key-id with the specific customer managed key ARN) enforces encryption at rest using that key. Option A (S3 Transfer Acceleration) only optimizes transfer speed, not encryption at rest. Option C (S3 Inventory) reports on encryption status but does not enforce it. Option D (default encryption with SSE-S3) uses S3-managed keys, not a customer managed KMS key, so it does not meet the requirement.

Answer

Enable S3 Transfer Acceleration to force encryption in transit.

Answer

Configure S3 Inventory to report on encryption status and alert on non-compliance.

Answer

Enable default encryption on the bucket with SSE-S3.

Question 4

A company uses AWS Lambda to process records from an Amazon Kinesis Data Stream. Each record is about 50 KB. The Lambda function transforms the data and writes to Amazon DynamoDB. Recently, the Lambda function has been experiencing throttling and high error rates. The Kinesis stream has 10 shards. What is the most cost-effective solution to improve processing throughput?

Accepted Answer

Increase the Batch Window (MaximumBatchingWindowInSeconds) for the event source mapping.. Increasing the Batch Window (MaximumBatchingWindowInSeconds) allows the Lambda function to accumulate more records from the Kinesis stream before invoking the function, reducing the number of invocations and thus lowering the chance of throttling. This is the most cost-effective solution as it does not require additional shards, memory, or parallelization, and directly addresses the high error rates caused by excessive concurrent executions.

Answer

Increase the number of shards in the Kinesis stream.

Answer

Increase the Parallelization Factor for the Lambda event source mapping.

Answer

Increase the memory allocated to the Lambda function.

Question 5

Which THREE factors should a data engineer consider when choosing between Amazon RDS and Amazon DynamoDB for a new application? (Choose THREE.)

Accepted Answer

Requirement for ACID transactions across multiple tables.. Amazon RDS (with engines like PostgreSQL or MySQL) supports ACID transactions across multiple tables, ensuring atomicity, consistency, isolation, and durability for complex operations. DynamoDB, while supporting transactions, is limited to a single AWS account and region, and its transactional API has constraints on item sizes and throughput, making RDS the better choice for multi-table ACID compliance.

Answer

Ability to encrypt data at rest.

Answer

Support for multi-region disaster recovery.

Question 6

A company needs to transform JSON data from Amazon Kinesis Data Streams into Parquet format and store it in Amazon S3. The transformation includes simple field mappings and type conversions. Which approach is most cost-effective and serverless?

Accepted Answer

Use Amazon Kinesis Data Firehose with an AWS Lambda function for transformation and output to Parquet. Amazon Kinesis Data Firehose can directly deliver streaming data to Amazon S3 in Parquet format. By attaching an AWS Lambda function for simple field mappings and type conversions, you achieve a fully serverless, cost-effective solution without managing any infrastructure. This approach minimizes costs because you pay only for the data volume processed by Firehose and the Lambda invocations, avoiding the overhead of always-on compute resources.

Answer

Use Amazon EC2 instances running Apache Spark Streaming

Answer

Use Amazon SageMaker for transformation

Answer

Use an AWS Glue ETL job triggered by a Kinesis stream

Question 7

A data engineer is designing a data ingestion pipeline for a social media analytics platform. The pipeline must ingest tweets in real-time, perform sentiment analysis, and store results in Amazon S3. The sentiment analysis is compute-intensive and must be done as the data arrives. The estimated throughput is 10,000 tweets per second. Which architecture is most suitable?

Accepted Answer

Amazon Kinesis Data Streams with Amazon Kinesis Data Analytics for sentiment analysis, then Kinesis Data Firehose to S3.. The most suitable because Amazon Kinesis Data Streams can ingest up to 10,000 records per second per shard (with shard-level scaling), and Kinesis Data Analytics provides built-in, low-latency stream processing for compute-intensive sentiment analysis using SQL or Apache Flink. Kinesis Data Firehose then reliably buffers and writes the processed results to Amazon S3 without custom code, ensuring near-real-time delivery.

Answer

Amazon SQS with AWS Lambda pollers to process tweets and store in S3.

Answer

Amazon EMR with Spark Streaming to process tweets and write to S3.

Answer

Amazon API Gateway with AWS Lambda to process each tweet and store in S3.

Question 8

A data engineer needs to ingest data from an Amazon S3 bucket into Amazon Redshift for analytics. The data is in CSV format and the Redshift table already exists. Which service can be used to perform this ingestion with minimal configuration?

Accepted Answer

Amazon Redshift COPY command. The Amazon Redshift COPY command is the most direct and minimal-configuration method to load data from an S3 bucket into an existing Redshift table. It is purpose-built for bulk data ingestion from S3, supports CSV format natively, and requires only the table name, S3 path, IAM role, and format options — no additional services or pipelines needed.

Answer

AWS Glue

Answer

Amazon Kinesis Data Firehose

Answer

AWS Database Migration Service (DMS)

Question 9

A data pipeline using AWS Glue ETL jobs is failing intermittently with the error 'Rate exceeded' when writing to an Amazon Redshift cluster. Which action is MOST effective to resolve this issue?

Accepted Answer

Enable auto-tuning on the Redshift cluster and use concurrency scaling.. Enabling auto-tuning on the Redshift cluster and using concurrency scaling dynamically adds cluster capacity to absorb spikes in write requests, directly addressing the 'Rate exceeded' error. This error typically occurs when the Glue ETL job's write throughput exceeds the cluster's current capacity, and concurrency scaling provides additional query queues to handle the load without manual intervention.

Answer

Increase the timeout of the Glue ETL job to allow more time for retries.

Answer

Disable workload management (WLM) concurrency scaling in Redshift.

Answer

Change the output file format from Parquet to CSV to reduce write size.

Question 10

A healthcare company processes patient records in near-real-time using Amazon Kinesis Data Streams. Each record contains sensitive personal health information (PHI). The data must be encrypted at rest and in transit. The company also needs to audit access to the data. The data engineer is designing the ingestion pipeline. Which combination of services and configurations meets these requirements?

Accepted Answer

Use Kinesis Data Streams with SSE-KMS and TLS, and enable CloudTrail for data events.. Kinesis Data Streams supports server-side encryption (SSE) using AWS KMS for at-rest encryption, and TLS for in-transit. CloudTrail can log Kinesis API calls for auditing. Option A lacks encryption at rest. Option B lacks auditing. Option D is wrong because S3 does not replace Kinesis for streaming.

Answer

Use Kinesis Data Firehose to deliver data to S3 with SSE-S3, and enable CloudTrail for S3.

Answer

Use Kinesis Data Streams with TLS and enable CloudTrail for auditing. Do not enable SSE.

Answer

Use Kinesis Data Streams with SSE-KMS and TLS. Do not enable any auditing.