A media company wants to improve a system that recommends media content to customer based on user behavior and preferences. To improve the recommendation system, the company needs to incorporate insights from third-party datasets into the company's existing analytics platform.
The company wants to minimize the effort and time required to incorporate third-party datasets.
Which solution will meet these requirements with the LEAST operational overhead?
To minimize effort and time required to incorporate third-party datasets into an existing analytics platform, it is best to use API calls to access and integrate these datasets. AWS Data Exchange is designed specifically for discovering and subscribing to third-party datasets, providing direct and easy integration. This service effectively reduces operational overhead because it directly supports these types of integrations without the need for complex configurations or additional infrastructure. AWS DataSync, on the other hand, is primarily intended for data transfer between on-premises storage and AWS storage services, not for directly accessing third-party datasets through APIs.
AWS DataSync is primarily used for data transfer services designed to simplify, automate, and accelerate moving data between on-premises storage systems and AWS storage services, as well as between different AWS storage services. Its primary role is not for accessing third-party datasets but for efficiently transferring large volumes of data. In contrast, AWS Data Exchange is designed specifically for discovering and subscribing to third-party data in the cloud, providing direct API access to these datasets, which aligns perfectly with the company's need to integrate this data into their recommendation systems with minimal overhead.
AWS Data Exchange is a service that makes it easy to share and manage data permissions from other organizations
A for me. "You can also discover and subscribe to new third-party data sets available through AWS Data Exchange" https://docs.aws.amazon.com/data-exchange/latest/userguide/what-is.html
A Data exchange is primarily designed for this purpose.
A is correct, DataSync doesn't really rely on API calls.
some relevant info: main: https://www.instapaper.com/read/1647436237
A Data exchange is primarily designed for this purpose.
A Data Exchange is the AWS official third-party datasets repository: https://aws.amazon.com/data-exchange
I will go with A. Kinesis Data Stram is more operational overhead.
A is correct
A is correct answer.
AWS DataExchange
options B, C, and D involve using Amazon Kinesis Data Streams or other services that may not be directly suited for integrating third-party datasets from external sources like AWS Data Exchange. These options might require additional configurations, data processing steps, or infrastructure management, resulting in higher operational overhead compared to directly leveraging AWS Data Exchange's capabilities through API calls (Option A).
I will go with A.
There is no info or guarantee this third-party dataset is available in AWS to be part of a data-share, hence the more assertive answer is B
Data Exchange is the AWS official third-party datasets repository: https://aws.amazon.com/data-exchange