100% Free Amazon DAS-C01 Practice Test Questions

Question 1

A data analyst is designing an Amazon QuickSight dashboard using centralized sales data that resides in Amazon Redshift. The dashboard must be restricted so that a salesperson in Sydney. Australia, can see only the Australia view and that a salesperson in New York can see only United States (US) data.

What should the data analyst do to ensure the appropriate data security is in place?

A : Place the data sources for Australia and the US into separate SPICE capacity pools.

B : Set up an Amazon Redshift VPC security group for Australia and the US.

C : Deploy QuickSight Enterprise edition to implement row-level security (RLS) to the sales table.

D : Deploy QuickSight Enterprise edition and set up different VPC security groups for Australia and the US.

Answer: D

Question 2

A company leverages Amazon Athena for ad-hoc queries against data stored in Amazon S3. The company wants to implement additional controls to separate query execution and query history among users, teams, or applications running in the same AWS account to comply with internal security policies.
Which solution meets these requirements?

A : Create an S3 bucket for each given use case, create an S3 bucket policy that grants permissions to appropriate individual IAM users. and apply the S3 bucket policy to the S3 bucket.

B : Create an Athena workgroup for each given use case, apply tags to the workgroup, and create an IAM policy using the tags to apply appropriate permissions to the workgroup.

C : Create an IAM role for each given use case, assign appropriate permissions to the role for the given use case, and add the role to associate the role with Athena.

D : Create an AWS Glue Data Catalog resource policy for each given use case that grants permissions to appropriate individual IAM users, and apply the resource policy to the specific tables used by Athena.

Answer: B

Question 3

A company ingests a large set of sensor data in nested JSON format from different sources and stores it in an Amazon S3 bucket. The sensor data must be joined with performance data currently stored in an Amazon Redshift cluster. A business analyst with basic SQL skills must build dashboards and analyze this data in Amazon QuickSight. A data engineer needs to build a solution to prepare the data for use by the business analyst. The data engineer does not know the structure of the JSON file. The company requires a solution with the least possible implementation effort. Which combination of steps will create a solution that meets these requirements? (Select THREE.)

A : Use an AWS Glue ETL job to convert the data into Apache Parquet format and write to Amazon S3.

B : Use an AWS Glue crawler to catalog the data.

C : Use an AWS Glue ETL job with the ApplyMapping class to un-nest the data and write to Amazon Redshift tables.

D : Use an AWS Glue ETL job with the Regionalize class to un-nest the data and write to Amazon Redshift tables.

E : Use QuickSight to create an Amazon Athena data source to read the Apache Parquet files in Amazon S3.

F : Use QuickSight to create an Amazon Redshift data source to read the native Amazon Redshift tables.

Answer: B,D,F

Question 4

A reseller that has thousands of AWS accounts receives AWS Cost and Usage Reports in an Amazon S3 bucket The reports are delivered to the S3 bucket in the following format
< examp/e-reporT-prefix >/< examp/e-report-rtame >/yyyymmdd-yyyymmdd/<examp/e-report-name> parquet
An AWS Glue crawler crawls the S3 bucket and populates an AWS Glue Data Catalog with a table Business analysts use Amazon Athena to query the table and create monthly summary reports for the AWS accounts The business analysts are experiencing slow queries because of the accumulation of reports from the last 5 years The business analysts want the operations team to make changes to improve query performance
Which action should the operations team take to meet these requirements?

A : Change the file format to csv.zip.

B : Partition the data by date and account ID

C : Partition the data by month and account ID

D : Partition the data by account ID, year, and month

Answer: B

Question 5

A data analyst is using Amazon QuickSight for data visualization across multiple datasets generated by applications. Each application stores files within a separate Amazon S3 bucket. AWS Glue Data Catalog is used as a central catalog across all application data in Amazon S3. A new application stores its data within a separate S3 bucket. After updating the catalog to include the new application data source, the data analyst created a new Amazon QuickSight data source from an Amazon Athena table, but the import into SPICE failed.
How should the data analyst resolve the issue?

A : Edit the permissions for the AWS Glue Data Catalog from within the Amazon QuickSight console.

B : Edit the permissions for the new S3 bucket from within the Amazon QuickSight console.

C : Edit the permissions for the AWS Glue Data Catalog from within the AWS Glue console.

D : Edit the permissions for the new S3 bucket from within the S3 console.

Answer: B

Free Practice Amazon DAS-C01 Exam Questions 2025