DEA-C01 Data Ingestion and Transformation Practice Test 13 — 15 Questions

Question 1

A company uses AWS Glue to run ETL jobs that process data from Amazon RDS to Amazon S3. The jobs run nightly and take 3 hours to complete. The data volume is growing by 20% each month. The engineer needs to reduce job runtime and cost. The source RDS is a db.r5.large instance. Which approach would be MOST effective?

Accepted Answer

Increase the number of Glue workers and choose a G.1X or G.2X worker type.. Option A is correct because increasing the number of Glue workers (DPUs) directly increases parallelism and reduces runtime, and you can choose a worker type with more memory if needed. Option B is wrong because RDS read replica does not help Glue processing speed. Option C is wrong because S3 Transfer Acceleration is for uploads, not Glue processing. Option D is wrong because reducing DPUs would increase runtime.

Answer

Reduce the number of DPUs to lower cost and accept longer runtime.

Answer

Create a read replica of the RDS instance and point the Glue job to the replica.

Answer

Enable S3 Transfer Acceleration on the destination bucket.

Question 2

A data engineer uses AWS DMS to migrate a 2 TB PostgreSQL database to Amazon Aurora PostgreSQL. The migration task is set to full load + CDC. After the full load completes, the CDC phase starts but shows a high latency of 5 minutes. The source database has a low write load. What should the engineer do to reduce the CDC latency?

Accepted Answer

Increase the size of the DMS replication instance.. Option B is correct because increasing the DMS replication instance size provides more memory and CPU for processing changes. Option A is wrong because disabling validation reduces overhead but not latency due to resource constraints. Option C is wrong because the source has low write load, so batch size is not the bottleneck. Option D is wrong because the source is PostgreSQL, not Oracle.

Answer

Decrease the batch size for the CDC task.

Answer

Disable the validation feature on the DMS task.

Answer

Enable logging for the DMS task to capture additional details.

Question 3

A company wants to ingest streaming data from thousands of IoT devices into AWS for real-time processing. Each device sends JSON payloads of about 2 KB at a rate of 1 message per second. The data must be processed with a durable, ordered stream per device. Which service should the company use as the ingestion layer?

Accepted Answer

Amazon Kinesis Data Streams.. Option C is correct because Kinesis Data Streams provides ordered data per shard, and shards can be partitioned by device ID. Option A is wrong because SQS does not guarantee order. Option B is wrong because Firehose is for delivery, not ordered processing. Option D is wrong because SNS is pub/sub and doesn't support ordered streams.

Answer

Amazon Simple Queue Service (Amazon SQS) with a FIFO queue.

Answer

Amazon Simple Notification Service (Amazon SNS) with a Lambda subscriber.

Answer

Amazon Kinesis Data Firehose with Direct Put.

Question 4

A company uses Amazon EMR to process large datasets stored in Amazon S3. The data is in Parquet format and partitioned by date. The EMR cluster uses Spark SQL for transformations. Recently, the job has been slow and some tasks are failing due to 'java.lang.OutOfMemoryError'. The cluster has 10 core nodes of type m5.xlarge. Which configuration change would MOST improve performance and stability?

Accepted Answer

Change the core node instance type to r5.xlarge (memory-optimized).. Option A is correct because using a memory-optimized instance type like r5.xlarge provides more memory per core. Option B is wrong because more partitions with same resources can cause overhead. Option C is wrong because increasing executor cores without increasing memory can worsen memory issues. Option D is wrong because Kryo serialization reduces memory for serialized objects, not OOM from processing.

Answer

Increase the number of Spark partitions using repartition(), but keep the same nodes.

Answer

Increase the number of executor cores in the Spark configuration.

Answer

Enable Kryo serialization in the Spark configuration.

Question 5

A data engineer is designing a data ingestion pipeline for real-time user activity logs. The logs are generated by a web application and must be ingested into Amazon S3 with minimal latency (under 1 minute). The logs also need to be queried in Amazon Athena. The engineer considers using Amazon Kinesis Data Firehose. Which TWO configurations are required to achieve near-real-time delivery to S3? (Choose TWO.)

Accepted Answer

Set the BufferIntervalInSeconds to 60 seconds.. Options A and D are correct. Set 'BufferIntervalInSeconds' to 60 seconds to flush every minute, and 'BufferSizeInMBs' to 1 MB to ensure small files are delivered quickly. Option B is wrong because enabling S3 compression does not affect delivery frequency. Option C is wrong because converting to Parquet is a transformation, not a delivery trigger. Option E is wrong because enabling error logging does not reduce latency.

Answer

Enable S3 compression (e.g., GZIP) on the delivery stream.

Answer

Enable Amazon CloudWatch error logging for the delivery stream.

Answer

Enable data format conversion to Parquet using AWS Glue.

Question 6

A company uses AWS Glue to run ETL jobs that transform data from Amazon S3 (Parquet) into a denormalized format for Amazon Redshift. The Glue job uses the DynamicFrame API. The job is failing with a 'MemoryError' when performing a join operation. The data is skewed on the join key. Which THREE actions can reduce memory usage and improve job stability? (Choose THREE.)

Accepted Answer

Use a broadcast join if one of the tables is small enough.. Options B, C, and D are correct. Salting the join key distributes skew, using broadcast join for a smaller table reduces shuffle, and splitting the job into multiple steps reduces memory per stage. Option A is wrong because increasing DPUs may help but is not a targeted solution. Option E is wrong because repartitioning does not fix skew and may increase overhead.

Answer

Increase the number of DPUs for the Glue job.

Answer

Repartition the data on the join key before the join operation.

Question 7

A company wants to ingest streaming data from thousands of IoT devices into AWS for real-time analytics. Which AWS service is best suited for this purpose?

Accepted Answer

Amazon Kinesis Data Streams. Amazon Kinesis Data Streams is designed for real-time streaming data ingestion from many sources. Option A is wrong because S3 is for object storage, not real-time streaming. Option B is wrong because Lambda processes data but is not a primary ingestion service. Option D is wrong because RDS is a relational database, not for streaming ingestion.

Answer

Amazon S3

Answer

AWS Lambda

Answer

Amazon RDS

Question 8

A data engineer needs to transform CSV files arriving in an S3 bucket into Parquet format and store them in another S3 bucket. The transformation is simple and on-demand, triggered by data arrival. Which solution is the MOST cost-effective and requires the least operational overhead?

Accepted Answer

Use S3 Events to trigger an AWS Lambda function that transforms the data. Option C is correct because S3 Events can trigger a Lambda function to perform the transformation when a new object is created. Option A is wrong because Glue jobs have startup time and cost more. Option B is wrong because EMR requires cluster management. Option D is wrong because Athena is for querying, not transforming.

Answer

Use Amazon EMR with Spark streaming

Answer

Use Amazon Athena to create a new table with Parquet format

Answer

Use AWS Glue ETL jobs scheduled to run every hour

Question 9

A company uses Kinesis Data Analytics for SQL-based real-time analytics on streaming data. They notice that the application is processing data slower than the incoming rate, causing increased latency. Which action is MOST likely to improve the throughput?

Accepted Answer

Increase the number of Kinesis Processing Units (KPUs) for the application. Option B is correct because increasing the number of Kinesis Processing Units (KPUs) allows more parallelism. Option A is wrong because decreasing the retention period does not affect processing speed. Option C is wrong because enabling auto-scaling for the stream itself does not increase application parallelism. Option D is wrong because increasing shards increases ingestion capacity, but the bottleneck is the analytics application.

Answer

Increase the number of shards in the Kinesis data stream

Answer

Enable auto-scaling on the Kinesis data stream

Answer

Decrease the retention period of the Kinesis data stream

Question 10

An organization needs to ingest data from on-premises databases into AWS S3 for archival purposes. The data volume is several TB per day, and the network has moderate bandwidth. Which AWS service is BEST suited for this bulk data transfer?

Accepted Answer

AWS DataSync. Option C is correct because AWS DataSync is designed for large-scale data transfers from on-premises to AWS. Option A is wrong because Snowball is for offline transfer, not real-time. Option B is wrong because Direct Connect is a dedicated network connection, not a data transfer service. Option D is wrong because S3 Transfer Acceleration speeds up uploads over the internet but is not specifically designed for on-premises bulk transfer.

Answer

AWS Direct Connect

Answer

Amazon S3 Transfer Acceleration

Answer

AWS Snowball

Question 11

A company uses AWS Glue for ETL jobs. The data engineer needs to ensure that the Glue job can access an S3 bucket in another account. What is the recommended approach?

Accepted Answer

Assign an IAM role to the Glue job with permissions to access the bucket, and configure the bucket policy to allow the role. Option A is correct because the Glue job's IAM role must have permissions to access the S3 bucket, and the bucket policy must allow the role. Option B is wrong because S3 bucket policies can allow cross-account access without requiring an IAM role in the other account. Option C is wrong because resource-based policies alone are not sufficient; the Glue job needs an IAM role with permissions. Option D is wrong because Glue jobs cannot use access keys; they use IAM roles.

Answer

Create an IAM role in the target account and have the Glue job assume that role

Answer

Configure the S3 bucket policy to allow the Glue job's IAM role and also set the Glue job's resource-based policy

Answer

Store AWS access keys for the target account in AWS Secrets Manager and have the Glue job retrieve them

Question 12

A data streaming application uses Kinesis Data Streams with 10 shards. The data producer is throttled frequently. Which action should be taken to resolve this issue?

Accepted Answer

Increase the number of shards. Option B is correct because increasing the number of shards increases the write capacity. Option A is wrong because decreasing retention period does not affect write throttling. Option C is wrong because enabling encryption does not affect throttling. Option D is wrong because using Enhanced Fan-Out is for consumers, not producers.

Answer

Decrease the data retention period

Answer

Use enhanced fan-out for consumers

Answer

Enable server-side encryption

Question 13

A company needs to transform JSON data from an S3 bucket into a structured format for Amazon Redshift. The transformation should be done serverlessly. Which service should be used?

Accepted Answer

AWS Glue. Option B is correct because AWS Glue is a serverless ETL service that can transform data for Redshift. Option A is wrong because Lambda can process events but is not ideal for large-scale ETL. Option C is wrong because Athena is a query service, not for transformation. Option D is wrong because EMR is not serverless.

Answer

Amazon EMR

Answer

Amazon Athena

Answer

AWS Lambda

Question 14

A company is ingesting data from multiple sources into S3 using AWS Glue. The data engineer notices that the Glue job is failing with an OutOfMemory error. Which step should be taken to resolve this issue?

Accepted Answer

Increase the number of DPUs allocated to the Glue job. Option C is correct because increasing the number of DPUs provides more memory. Option A is wrong because reducing data volume is not a solution. Option B is wrong because using a smaller file size may help but not directly address memory. Option D is wrong because Glue does not support memory configuration directly.

Answer

Reduce the volume of incoming data

Answer

Configure the job to use a larger memory setting

Answer

Use a smaller file size for input

Question 15

A company needs to ingest real-time clickstream data from a web application into Amazon Redshift with minimal latency. The data volume is high and requires processing before loading. Which architecture is MOST appropriate?

Accepted Answer

Kinesis Data Streams -> Kinesis Data Firehose -> Redshift. Option A is correct because Kinesis Data Firehose can deliver streaming data to Redshift with built-in transformation via Lambda. Option B is wrong because S3 does not provide real-time ingestion. Option C is wrong because Glue is batch-oriented. Option D is wrong because DynamoDB Streams is for DynamoDB changes, not clickstream.

Answer

AWS Glue ETL jobs scheduled every 5 minutes -> Redshift

Answer

S3 -> Lambda -> Redshift

Answer

DynamoDB Streams -> Lambda -> Redshift