AWS Data Exchange for Third-Party Datasets

DEA-C01 By islever Editorial Last updated

Perform data ingestion.

Short answer

A Use API calls to access and integrate third-party datasets from AWS Data Exchange.

Question

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?
  1. Use API calls to access and integrate third-party datasets from AWS Data Exchange. Correct Answer
  2. Use API calls to access and integrate third-party datasets from AWS DataSync.
  3. Use Amazon Kinesis Data Streams to access and integrate third-party datasets from AWS CodeCommit repositories.
  4. Use Amazon Kinesis Data Streams to access and integrate third-party datasets from Amazon Elastic Container Registry (Amazon ECR).

Key Takeaways

The core concept is identifying the purpose of AWS Data Exchange versus other data transfer or storage services. The common trap is confusing Data Exchange with DataSync or Kinesis due to similar-sounding names or overlapping data movement capabilities.

This question tests the correct selection of AWS services for integrating third-party data with minimal operational overhead. The correct solution leverages AWS Data Exchange, a fully managed service designed specifically for discovering and subscribing to third-party datasets.

Common mistake: Option B (AWS DataSync) is often chosen incorrectly because candidates associate it with 'data transfer.' However, DataSync is for moving large volumes of data between on-premises and AWS storage, not for accessing curated third-party datasets via API in an analytics context.

Expert Analysis

Why the Answer Is Correct

AWS Data Exchange is a fully managed data exchange service that makes it easy to find, subscribe to, use, and manage third-party data from various sources. It allows customers to integrate external data directly into their analytics platforms with minimal operational overhead, as it handles the security, licensing, and distribution aspects. Using API calls to access this data fits the requirement for seamless integration.

Why the Other Options Are Wrong

Option B is incorrect because AWS DataSync is designed for automating data transfer between on-premises storage and AWS storage services (like S3 or EFS), not for accessing third-party datasets. Option C is wrong because Amazon CodeCommit is a source control service for Git repositories, unrelated to third-party data ingestion. Option D is incorrect because Amazon ECR stores Docker container images, which are not third-party datasets for analytics.

Community Comment Notes

Community consensus strongly supports A, with many users noting that Data Exchange is the official AWS repository for third-party data. One user highlighted that DataSync relies less on direct API calls for dataset discovery compared to Data Exchange's subscription model. Another comment reinforced that Kinesis is more operationally complex for this specific use case.

Official Reference

https://docs.aws.amazon.com/data-exchange/latest/userguide/what-is.html

This link opens the official vendor documentation in a new tab.

Exam Strategy

Always map the type of data source to the appropriate AWS service. For 'third-party datasets' or 'marketplace data,' think AWS Data Exchange immediately. For moving bulk files between locations, think DataSync or Transfer Family.

Frequently Asked Questions

Why is AWS DataSync not suitable for third-party datasets?

DataSync is for transferring data between storage systems (on-prem to AWS), not for discovering or subscribing to external third-party data catalogs.

What is the primary difference between Data Exchange and Data Sync?

Data Exchange focuses on finding and using third-party data subscriptions, while DataSync focuses on automated data transfer tasks between storage endpoints.

More DEA-C01 FAQ →

Community Votes

A
100%

100% of anonymous learners picked answer A. Votes are pick records left by other test-takers — they are not the verified answer.

Discussion 15 contributions

Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.

From public community threads 15

  1. KelvinPun 👍 13 Answered A
    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.
  2. hsnin 👍 4 Answered A
    AWS Data Exchange is a service that makes it easy to share and manage data permissions from other organizations
  3. GiorgioGss 👍 3 Answered A
    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
  4. lalitjhawar 👍 3
    A Data Exchange is the AWS official third-party datasets repository: https://aws.amazon.com/data-exchange
  5. ttpro1995 👍 3 Answered A
    Yeah, AWS want people to buy data from their marketplace. So, ... you know.
Show 10 more comments
  1. Josa2 👍 2 Answered B
    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
  2. sudohogan 👍 2
    A is correct, DataSync doesn't really rely on API calls.
  3. ceramem 👍 2
    A Data exchange is primarily designed for this purpose.
  4. k350Secops 👍 1 Answered A
    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).
  5. lunachi4 👍 1 Answered A
    I will go with A. Kinesis Data Stram is more operational overhead.
  6. Shubham1989 👍 1
    Should be AWS Data Exchange.
  7. nanaw770 👍 1 Answered A
    A is correct answer.
  8. kj07 👍 1
    I will go with A.
  9. 0060594 👍 1 Answered A
    AWS DataExchange
  10. Manohar24 👍 1 Answered A
    A is correct

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