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Answer: Create an analysis in Amazon QuickSight. Connect all the data sources and create new datasets. Publish dashboards to visualize the data. Share the dashboards with the appropriate users and groups.
## Explanation **Correct Answer: B** **Why Option B is correct:** 1. **Amazon QuickSight** is AWS's business intelligence and data visualization service, which is specifically designed for creating interactive dashboards and reports. 2. QuickSight can connect to multiple data sources including Amazon S3 and Amazon RDS for PostgreSQL, allowing all data sources within the data lake to be included. 3. QuickSight provides granular access control where dashboards can be shared with specific users and groups, enabling: - Full access for the management team - Limited access for the rest of the company 4. QuickSight's sharing capabilities allow for different permission levels (viewer, editor, owner) which aligns with the requirement for different access levels. **Why Option A is incorrect:** - While QuickSight can integrate with IAM roles, sharing dashboards with IAM roles is less granular than sharing with specific users and groups. QuickSight's primary sharing mechanism is through users and groups within the QuickSight account. **Why Option C is incorrect:** - AWS Glue with S3 publishing creates static reports, not interactive visualizations. - S3 bucket policies provide limited access control compared to QuickSight's fine-grained permissions. - This approach doesn't provide the interactive data visualization capabilities required. **Why Option D is incorrect:** - Similar to Option C, this creates static reports in S3 rather than interactive visualizations. - Amazon Athena is for querying data, not for creating interactive dashboards. - S3 bucket policies don't provide the same level of granular access control as QuickSight. **Key AWS Services Involved:** - **Amazon QuickSight**: Business intelligence and visualization service - **Amazon S3**: Data storage for the data lake - **Amazon RDS for PostgreSQL**: Relational database component of the data lake - **IAM**: Identity and Access Management for overall AWS security **Best Practice:** When requiring interactive data visualizations with different access levels for different user groups, Amazon QuickSight is the appropriate AWS service as it's specifically designed for this purpose.
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A company hosts a data lake on AWS. The data lake consists of data in Amazon S3 and Amazon RDS for PostgreSQL. The company needs a reporting solution that provides data visualization and includes all the data sources within the data lake. Only the company's management team should have full access to all the visualizations. The rest of the company should have only limited access.
Which solution will meet these requirements?
A
Create an analysis in Amazon QuickSight. Connect all the data sources and create new datasets. Publish dashboards to visualize the data. Share the dashboards with the appropriate IAM roles.
B
Create an analysis in Amazon QuickSight. Connect all the data sources and create new datasets. Publish dashboards to visualize the data. Share the dashboards with the appropriate users and groups.
C
Create an AWS Glue table and crawler for the data in Amazon S3. Create an AWS Glue extract, transform, and load (ETL) job to produce reports. Publish the reports to Amazon S3. Use S3 bucket policies to limit access to the reports.
D
Create an AWS Glue table and crawler for the data in Amazon S3. Use Amazon Athena Federated Query to access data within Amazon RDS for PostgreSQL. Generate reports by using Amazon Athena. Publish the reports to Amazon S3. Use S3 bucket policies to limit access to the reports.