Data is the most fundamental factor that provides businesses a competitive edge in the market. It is a strategic asset that you can leverage to gain insights, identify upcoming profitable trends, and make informed decisions. 

However, procuring the right data can be challenging. Traditional methods often involve complex negotiations, manual integrations, and compatibility issues. Here’s where the AWS Marketplace Data Exchange comes into the picture. It is a secure and streamlined marketplace for exchanging third-party datasets within the AWS cloud. 

This article will help you understand AWS Marketplace Data Exchange, including its features, benefits, and more. 

What is AWS Marketplace Data Exchange? 

AWS Data Exchange is a cloud service that simplifies the sharing and managing data entitlements across organizations. It is a central hub that connects data receivers and data senders. 

AWS Marketplace Data Exchange: How the AWS Marketplace Data Exchange works 
AWS Marketplace Data Exchange: How the AWS Marketplace Data Exchange works 

As a data receiver, you can seamlessly browse various datasets organized in a centralized catalog. It eliminates the need to find and negotiate with individual data providers. Once you find relevant datasets, you can subscribe and integrate them directly into your existing workflows to fully realize the potential of your data strategies.

You can also use this service as a data sender to publish datasets to a large audience of potential customers on the AWS cloud. It takes care of all the complexities of data delivery, subscriptions, and billing, allowing you to focus on curating and maintaining your datasets.   

AWS Marketplace prioritizes responsible data exchange by maintaining transparency and a rigorous review process for permitted data types. The platform safeguards users by limiting providers to datasets that meet the legal requirements outlined in the AWS Marketplace Seller Terms and Conditions. Let’s delve into how AWS Data Exchange organizes your data.   

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Data Architecture of AWS Data Exchange 

AWS Data Exchange stores your data in a hierarchical structure with three main components: datasets, revisions, and assets.

  • Datasets: They are containers holding the data you want to share, access, or update over time. 
  • Revisions: Since datasets are dynamic, revisions act like versions within a dataset. Each revision contains at least one asset and represents specific data at a particular point in time. It allows data senders to update data without affecting the historical versions.
  • Assets: This part contains the actual data. It is the fundamental building block that makes up revisions. An asset can be in various formats, such as a structured data file (CSV, JSON) in S3, an image file, an API endpoint, or even access permissions to specific data in AWS Lake Formation. 

You can create, view, update, and delete datasets by using any one of the four ways:

  • AWS Data Exchange Console: AWS provides a web interface for easy data management. It is like a visual dashboard for controlling your datasets. 
  • AWS Command Line Interface (CLI): If you prefer to use commands, the AWS CLI provides a set of commands to manage your data. 
  • REST Client: As a developer, you can use your own REST client to interact with the AWS Data Exchange API and programmatically control your datasets.
  • AWS Software Development Kits (SDKs): AWS provides SDKs for several programming languages. It includes Python, Java, and Node.js. These SDKs allow you to integrate dataset management functionalities into your applications.

Key Advantages of AWS Data Exchange 

AWS Marketplace Data Exchange offers many features to enhance your user experience. Let’s look at how it streamlines the process:

  • Extensive Dataset Catalog: The catalog provides the latest data products relevant to finance, healthcare, geospatial, media and entertainment, consumer, and other industries. You can also browse AWS Marketplace’s vast collection of 1000+ free and open data products from government bodies, research establishments, academic institutions, and private enterprises. 
  • Seamless Integration with AWS Services: A key advantage of AWS Data Exchange is its integration with other AWS Services. Once you subscribe to a data product, you can load the data directly into your Amazon S3 storage bucket. Then, you can analyze it using various AWS services like Amazon Redshift or Amazon SageMaker, streamlining your data workflow.
  • Secure Data Exchange Environment: Security is a major concern when dealing with data. AWS Data Exchange prioritizes security by encrypting all your data in transit and at rest. It also offers features like subscription verification and audit logs to ensure authorized access and maintain your data’s integrity.
  • Options for Data Providers: If you’re a data provider, AWS Data Exchange offers features to simplify sharing your data. You can quickly list your data products and reach a broad audience of potential customers. It also allows you to set custom offer terms, create private data products for specific customers, and leverage reporting tools to track your product’s performance. 

Overall, AWS Marketplace Data Exchange is a comprehensive and convenient platform with 3500+ datasets at your disposal. It is a cost-effective, scalable, and flexible solution that provides quality data for personal use or collaboration. 

Now that you have your datasets, your next step will be to consolidate and move the data to your warehouse for analysis. In the next section, you will learn how Hevo, a data integration platform, can help you.

Simplified Data Integration with Hevo

Once you have obtained data from AWS Marketplace Data Exchange, you can utilize its full potential by efficiently analyzing it to derive actionable insights. This is where data integration comes into the picture. The process entails collecting data from various sources, transforming it into standardized formats, and loading it into a central repository like a data warehouse or lake. A refined view of your data leads to powerful analytics and provides a deeper understanding of subjects related to your business. 

AWS Marketplace Data Exchange: Data Integration Process Image Source
AWS Marketplace Data Exchange: Data Integration Process

Hevo is a real-time ELT (Extract, Load, and Transform) data integration platform that offers over 150 data sources to help you set up cost-effective and automated data pipelines. You can extract valuable data from your AWS Data Exchange and move it to your desired destination, helping you save time and resources with reduced risk of errors. 

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However, the datasets you obtain aren’t always ready for analysis in their raw format. Hevo understands this and enables you to perform data transformations directly within the pipelines. It includes cleaning, filtering, and enriching your data to meet your requirements. You can comfortably use its intuitive no-code visual interface for data transformation, even with limited technical expertise.   

With its extensive features, you can monitor your data pipelines, identify issues, and address them before they impact your data flow. The error-handling mechanisms ease your job by notifying you of errors and streamlining the troubleshooting process. You can understand the origin and keep track of each data transformation using the data lineage tracking functionality.  

Through data integration processes, you can seamlessly prepare your data for effective analysis. For more information, you can refer to Hevo’s documentation. Now, let’s explore some practical use cases where you can render the AWS Data Exchange service. 

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AWS Marketplace Data Exchange: Use Cases 

Here are a few examples of industries in which you can use third-party data provided by AWS Marketplace Data Exchange to achieve better results:

  • Healthcare and Pharmaceuticals: You can identify trends or patterns in disease progression, drug effectiveness, and potential risk factors by accessing anonymized patient datasets and clinical trial results. You can expedite the research process and lead to faster development of new treatments.
  • Supply Chain Optimization: You can integrate data on suppliers, raw material availability, and consumer demand to forecast your inventory needs accurately. By utilizing geospatial and logistics datasets, you can optimize delivery routes and manage transportation costs.
  • Marketing Research: Incorporating third-party consumer datasets can help you better understand your target audience and market trends. You can gain insights into demographics, buying behavior, and competitor analysis to formulate effective marketing strategies. 

Beyond these examples, AWS Marketplace Data Exchange empowers businesses across various sectors to leverage third-party datasets for better decision-making and innovation.

Wrapping Up 

In this article, you explored AWS Marketplace Data Exchange, its features, and a few use cases for utilizing third-party datasets. You have also learned why data integration is important and how you can achieve it using Hevo’s pre-built connectors. With the large number of datasets available on AWS Data Exchange and the integration capabilities of Hevo, you can take your business projects to the next level. 

Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite firsthand.

Share your experience of AWS Marketplace Data Exchange in the comments section below!


Q. How do you use API subscriptions from AWS Data Exchange?

You can use API subscriptions from AWS Data Exchange by following the steps below:

  • Subscribe to an API: Browse the AWS Marketplace Data Exchange catalog and find the specific API you are interested in. Once you’ve found the API you want to use, select it and proceed to subscribe to it. This might involve choosing a specific offer and reviewing terms before finalizing the subscription.
  • Using the Subscribed API: You can refer to the AWS Data Exchange documentation for more information. 
Riya Bothra
Technical Writer, Hevo Data

Riya is a technical content writer who enjoys writing informative blogs and insightful guides on data engineering. An avid reader, she is committed to staying abreast of the latest developments in the data analytics domain.

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