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Answer: In the AWS account of the company that produces the data, create an AWS Data Exchange datashare by connecting AWS Data Exchange to the Redshift cluster. Configure subscription verification. Require the data customers to subscribe to the data product.
By choosing option B, the company is leveraging AWS Data Exchange to effectively manage and distribute data to its customers while maintaining security and identity verification. Here are the key elements that make this solution appropriate: 1. **AWS Data Exchange Integration**: By using AWS Data Exchange directly, the company can create a data product that encapsulates the Redshift data, significantly simplifying the process of distributing this data to a large number of customers. 2. **Amazon Redshift Datashare**: AWS Data Exchange can create datashares by connecting directly to a Redshift cluster. This eliminates the need for intermediate steps such as downloading and uploading data, which reduces operational overhead. 3. **Subscription Verification**: AWS Data Exchange supports subscription verification, allowing the company to confirm the identities of data customers before granting them access. This ensures that the company can control who has access to their data, maintaining security and compliance. 4. **Real-Time Data Access**: By directly connecting AWS Data Exchange to the Redshift cluster, customers will always have access to the most recent data without the need for periodic updates or manual uploads. This continuous data availability is crucial for providing timely and accurate information to customers. Overall, this approach minimizes the manual management of data distribution and leverages AWS's managed services to ensure data security, identity verification, and real-time access, reducing operational burden significantly.
Author: LeetQuiz Editorial Team
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A company runs an application on AWS. The company curates data from several different sources. The company uses proprietary algorithms to perform data transformations and aggregations. After the company performs ETL processes, the company stores the results in Amazon Redshift tables. The company sells this data to other companies. The company downloads the data as files from the Amazon Redshift tables and transmits the files to several data customers by using FTP. The number of data customers has grown significantly. Management of the data customers has become difficult. The company will use AWS Data Exchange to create a data product that the company can use to share data with customers. The company wants to confirm the identities of the customers before the company shares data. The customers also need access to the most recent data when the company publishes the data. Which solution will meet these requirements with the LEAST operational overhead?
A
Use AWS Data Exchange for APIs to share data with customers. Configure subscription verification. In the AWS account of the company that produces the data, create an Amazon API Gateway Data API service integration with Amazon Redshift. Require the data customers to subscribe to the data product.
B
In the AWS account of the company that produces the data, create an AWS Data Exchange datashare by connecting AWS Data Exchange to the Redshift cluster. Configure subscription verification. Require the data customers to subscribe to the data product.
C
Download the data from the Amazon Redshift tables to an Amazon S3 bucket periodically. Use AWS Data Exchange for S3 to share data with customers. Configure subscription verification. Require the data customers to subscribe to the data product.
D
Publish the Amazon Redshift data to an Open Data on AWS Data Exchange. Require the customers to subscribe to the data product in AWS Data Exchange. In the AWS account of the company that produces the data, attach IAM resource- based policies to the Amazon Redshift tables to allow access only to verified AWS accounts.
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