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.

Comment: *

Name: *

Email: *

Verification: *

A company has a marketing department and a finance department. The departments are storing data in Amazon S3 in their own AWS accounts in AWS Organizations. Both departments use AWS Lake Formation to catalog and secure their data. The departments have some databases and tables that share common names.
The marketing department needs to securely access some tables from the finance department.
Which two steps are required for this process? (Choose two.)

• A.The finance department grants Lake Formation permissions for the tables to the external account for the marketing department.
• B.The finance department creates cross-account IAM permissions to the table for the marketing department role.
• C.The marketing department creates an IAM role that has permissions to the Lake Formation tables.

Comment: *

Name: *

Email: *

Verification: *

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.Deploy QuickSight Enterprise edition and set up different VPC security groups for Australia and the US.
• B.Deploy QuickSight Enterprise edition to implement row-level security (RLS) to the sales table.
• C.Place the data sources for Australia and the US into separate SPICE capacity pools.
• D.Set up an Amazon Redshift VPC security group for Australia and the US.

Comment: *

Name: *

Email: *

Verification: *

A company that monitors weather conditions from remote construction sites is setting up a solution to collect temperature data from the following two weather stations.
* Station A, which has 10 sensors
* Station B, which has five sensors
These weather stations were placed by onsite subject-matter experts.
Each sensor has a unique ID. The data collected from each sensor will be collected using Amazon Kinesis Data Streams.
Based on the total incoming and outgoing data throughput, a single Amazon Kinesis data stream with two shards is created. Two partition keys are created based on the station names. During testing, there is a bottleneck on data coming from Station A, but not from Station B.
Upon review, it is confirmed that the total stream throughput is still less than the allocated Kinesis Data Streams throughput.
How can this bottleneck be resolved without increasing the overall cost and complexity of the solution, while retaining the data collection quality requirements?

• A.Increase the number of shards in Kinesis Data Streams to increase the level of parallelism.
• B.Create a separate Kinesis data stream for Station A with two shards, and stream Station A sensor data to the new stream.
• C.Reduce the number of sensors in Station A from 10 to 5 sensors.
• D.Modify the partition key to use the sensor ID instead of the station name.

Comment: *

Name: *

Email: *

Verification: *

A company that monitors weather conditions from remote construction sites is setting up a solution to collect temperature data from the following two weather stations.
Station A, which has 10 sensors
Station B, which has five sensors
These weather stations were placed by onsite subject-matter experts.
Each sensor has a unique ID. The data collected from each sensor will be collected using Amazon Kinesis Data Streams.
Based on the total incoming and outgoing data throughput, a single Amazon Kinesis data stream with two shards is created. Two partition keys are created based on the station names. During testing, there is a bottleneck on data coming from Station A, but not from Station B.
Upon review, it is confirmed that the total stream throughput is still less than the allocated Kinesis Data Streams throughput.
How can this bottleneck be resolved without increasing the overall cost and complexity of the solution, while retaining the data collection quality requirements?

• A.Increase the number of shards in Kinesis Data Streams to increase the level of parallelism.
• B.Create a separate Kinesis data stream for Station A with two shards, and stream Station A sensor data to the new stream.
• C.Modify the partition key to use the sensor ID instead of the station name.
• D.Reduce the number of sensors in Station A from 10 to 5 sensors.

Comment: *

Name: *

Email: *

Verification: *