Free Amazon DAS-C01 Exam Actual Questions & Explanations

Name: AWS Certified Data Analytics - Specialty
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SKU: DAS-C01
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Last updated on: Jun 3, 2026

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Question No. 1

A company hosts its analytics solution on premises. The analytics solution includes a server that collects log files. The analytics solution uses an Apache Hadoop cluster to analyze the log files hourly and to produce output files. All the files are archived to another server for a specified duration.

The company is expanding globally and plans to move the analytics solution to multiple AWS Regions in the AWS Cloud. The company must adhere to the data archival and retention requirements of each country where the data is stored.

Which solution will meet these requirements?

ACreate an Amazon S3 bucket in one Region to collect the log files. Use S3 event notifications to invoke an AWS Glue job for log analysis. Store the output files in the target S3 bucket. Use S3 Lifecycle rules on the target S3 bucket to set an expiration period that meets the retention requirements of the country that contains the Region.

BCreate a Hadoop Distributed File System (HDFS) file system on an Amazon EMR cluster in one Region to collect the log files. Set up a bootstrap action on the EMR cluster to run an Apache Spark job. Store the output files in a target Amazon S3 bucket. Schedule a job on one of the EMR nodes to delete files that no longer need to be retained.

CCreate an Amazon S3 bucket in each Region to collect log files. Create an Amazon EMR cluster. Submit steps on the EMR cluster for analysis. Store the output files in a target S3 bucket in each Region. Use S3 Lifecycle rules on each target S3 bucket to set an expiration period that meets the retention requirements of the country that contains the Region.

DCreate an Amazon Kinesis Data Firehose delivery stream in each Region to collect log data. Specify an Amazon S3 bucket in each Region as the destination. Use S3 Storage Lens for data analysis. Use S3 Lifecycle rules on each destination S3 bucket to set an expiration period that meets the retention requirements of the country that contains the Region.

Show Answer

Correct Answer: C

Question No. 2

A gaming company is building a serverless data lake. The company is ingesting streaming data into Amazon Kinesis Data Streams and is writing the data to Amazon S3 through Amazon Kinesis Data Firehose. The company is using 10 MB as the S3 buffer size and is using 90 seconds as the buffer interval. The company runs an AWS Glue ET L job to merge and transform the data to a different format before writing the data back to Amazon S3.

Recently, the company has experienced substantial growth in its data volume. The AWS Glue ETL jobs are frequently showing an OutOfMemoryError error.

Which solutions will resolve this issue without incurring additional costs? (Select TWO.)

APlace the small files into one S3 folder. Define one single table for the small S3 files in AWS Glue Data Catalog. Rerun the AWS Glue ET L jobs against this AWS Glue table.

BCreate an AWS Lambda function to merge small S3 files and invoke them periodically. Run the AWS Glue ETL jobs after successful completion of the Lambda function.

CRun the S3DistCp utility in Amazon EMR to merge a large number of small S3 files before running the AWS Glue ETL jobs.

DUse the groupFiIes setting in the AWS Glue ET L job to merge small S3 files and rerun AWS Glue E TL jobs.

EUpdate the Kinesis Data Firehose S3 buffer size to 128 MB. Update the buffer interval to 900 seconds.

Show Answer

Correct Answer: A, D

The groupFiles setting is a feature of AWS Glue that enables an ETL job to group files when they are read from an Amazon S3 data store.This can reduce the number of ETL tasks and in-memory partitions, and improve the performance and memory efficiency of the job1. By using the groupFiles setting in the AWS Glue ETL job, the gaming company can merge small S3 files and avoid the OutOfMemoryError error.

The Kinesis Data Firehose S3 buffer size and buffer interval are parameters that determine how much data is buffered before delivering it to Amazon S3.Increasing the buffer size and buffer interval can result in larger files being delivered to Amazon S3, which can reduce the number of small files and improve the performance of downstream processing2. By updating the Kinesis Data Firehose S3 buffer size to 128 MB and buffer interval to 900 seconds, the gaming company can create fewer, larger S3 files and avoid the OutOfMemoryError error.

Question No. 3

A company uses Amazon EC2 instances to receive files from external vendors throughout each day. At the end of each day, the EC2 instances combine the files into a single file, perform gzip compression, and upload the single file to an Amazon S3 bucket. The total size of all the files is approximately 100 GB each day.

When the files are uploaded to Amazon S3, an AWS Batch job runs a COPY command to load the files into an Amazon Redshift cluster.

Which solution will MOST accelerate the COPY process?

AUpload the individual files to Amazon S3. Run the COPY command as soon as the files become available.

BSplit the files so that the number of files is equal to a multiple of the number of slices in the Redshift cluster. Compress and upload the files to Amazon S3. Run the COPY command on the files.

CSplit the files so that each file uses 50% of the free storage on each compute node in the Redshift cluster. Compress and upload the files to Amazon S3. Run the COPY command on the files.

Dpply sharding by breaking up the files so that the DISTKEY columns with the same values go to the same file. Compress and upload the sharded files to Amazon S3. Run the COPY command on the files.

Show Answer

Correct Answer: B

Question No. 4

A company wants to improve user satisfaction for its smart home system by adding more features to its recommendation engine. Each sensor asynchronously pushes its nested JSON data into Amazon Kinesis Data Streams using the Kinesis Producer Library (KPL) in Jav

a. Statistics from a set of failed sensors showed that, when a sensor is malfunctioning, its recorded data is not always sent to the cloud.

The company needs a solution that offers near-real-time analytics on the data from the most updated sensors. Which solution enables the company to meet these requirements?

ASet the RecordMaxBufferedTime property of the KPL to '1' to disable the buffering on the sensor side. Use Kinesis Data Analytics to enrich the data based on a company-developed anomaly detection SQL script. Push the enriched data to a fleet of Kinesis data streams and enable the data transformation feature to flatten the JSON file. Instantiate a dense storage Amazon Redshift cluster and use it as the destination for the Kinesis Data Firehose delivery stream.

BUpdate the sensors code to use the PutRecord/PutRecords call from the Kinesis Data Streams API with the AWS SDK for Java. Use Kinesis Data Analytics to enrich the data based on a company-developed anomaly detection SQL script. Direct the output of KDA application to a Kinesis Data Firehose delivery stream, enable the data transformation feature to flatten the JSON file, and set the Kinesis Data Firehose destination to an Amazon Elasticsearch Service cluster.

CSet the RecordMaxBufferedTime property of the KPL to '0' to disable the buffering on the sensor side. Connect for each stream a dedicated Kinesis Data Firehose delivery stream and enable the data transformation feature to flatten the JSON file before sending it to an Amazon S3 bucket. Load the S3 data into an Amazon Redshift cluster.

DUpdate the sensors code to use the PutRecord/PutRecords call from the Kinesis Data Streams API with the AWS SDK for Java. Use AWS Glue to fetch and process data from the stream using the Kinesis Client Library (KCL). Instantiate an Amazon Elasticsearch Service cluster and use AWS Lambda to directly push data into it.

Show Answer

Correct Answer: B

https://docs.aws.amazon.com/streams/latest/dev/developing-producers-with-kpl.html

The KPL can incur an additional processing delay of up to RecordMaxBufferedTime within the library (user-configurable). Larger values of RecordMaxBufferedTime results in higher packing efficiencies and better performance. Applications that cannot tolerate this additional delay may need to use the AWS SDK directly.

Question No. 5

A retail company leverages Amazon Athena for ad-hoc queries against an AWS Glue Data Catalog. The data analytics team manages the data catalog and data access for the company. The data analytics team wants to separate queries and manage the cost of running those queries by different workloads and teams. Ideally, the data analysts want to group the queries run by different users within a team, store the query results in individual Amazon S3 buckets specific to each team, and enforce cost constraints on the queries run against the Data Catalog.

Which solution meets these requirements?

ACreate IAM groups and resource tags for each team within the company. Set up IAM policies that control
user access and actions on the Data Catalog resources.

BCreate Athena resource groups for each team within the company and assign users to these groups. Add S3 bucket names and other query configurations to the properties list for the resource groups.

CCreate Athena workgroups for each team within the company. Set up IAM workgroup policies that control user access and actions on the workgroup resources.

DCreate Athena query groups for each team within the company and assign users to the groups.

Show Answer

Correct Answer: C

https://aws.amazon.com/about-aws/whats-new/2019/02/athena_workgroups/