Introducing the Snowflake Data Cloud: Data Exchange


Introducing the Snowflake Data Cloud: Data Exchange

This series highlights how Snowflake excels across different data workloads through a new cloud data platform that organizations can trust and rely on as they move into the future.

Have you ever been working on a project and wanted to pull in some data that you didn’t have access to? This has happened to me on far too many occasions. My next step is to figure out where I am going to get that data from then how I am going to bring it in for analysis. The whole process is cumbersome and extremely time-consuming. What if we could have data that is ready for immediate use? This idea is something that would have been laughable in the past, but in the world of the cloud, it can be our reality.  

There Is Always More Data

Snowflake’s data exchange opens the doors to what is possible with shared data. Not only can we optimize time spent extracting this data in the traditional sense, but we can also look at data completely differently—as an asset that could potentially be monetized. A data exchange is like any other marketplace where consumers and sellers exchange a good or service; in this case, it’s data. And as we all know, there is always more data. 

Data exchanges present multiple solutions to consumers and businesses alike. Businesses are able to share data with consumers easily through an exchange, and consumers can easily access data without the cumbersome process of creating an ETL pipeline or extracting data from an FTP server. Currently, for a consumer to pull in one source and prep it for use, it could take up to two weeks of time, and that’s assuming you are using the best-in-class tools for the job. Snowflake’s data exchange offers data that is easily accessible for consumers and decreases the time it takes to find solutions and implement effective change inside of organizations. The world of data integrations has been overdue for a change. Luckily, Snowflake has designed a solution. 

The Snowflake Data Exchange 

The first use case for the data exchange is data consumers: organizations who want to use data from an external source alongside their proprietary data. By leveraging Snowflake’s data exchange, consumers are able to instantaneously consume live data from providers. The moment data is changed from a provider, it is reflected in the share, ensuring that consumers are always operating with the most up-to-date data. This is made possible by Snowflake’s unique cloud-first architecture and isolated cloud storage.  

Unlike traditional data-sharing patterns where organizations share a copy of their data, the Snowflake data exchange gives consumers access directly to your underlying tables—there are no copies of the data circulating around, and you can revoke access in an instant. By provisioning access to the direct table, we can govern its use in a way that was impossible with legacy architectures. Instead of canceling an FTP service and knowing the copies of data up to that point have been extracted and saved outside of your organization, we can remove a consumer’s access to Snowflake’s share, revoking access immediately.  

We can access this data easily, but what is even there? Fortunately, through the data exchange, we will have access to the numerous public and private datasets in the Snowflake marketplace. Here, you can easily pull in datasets focusing on weather, travel, housing and more. 

Sharing Data with Customers 

The data exchange is also valuable to another workload: our data producers. Data producers are organizations who have valuable datasets and provide them to external users via the Snowflake data exchange. Organizations can easily share their datasets with Snowflake users. Using the power of Snowflake, they are easily able to sell direct access to their ready-to-use data, as well as market themselves to find potential customers.  

Using this best-in-class data warehouse allows you to bring your customers alongside you in leveraging the power of Snowflake. Offering access to your data in such a seamless fashion helps them make more informed decisions and begin seeing value in their investment in you immediately, not after a project completes to get them the data. From a cost perspective, the economics on both sides of the equation makes so much sense: Snowflake’s multi-clustered, shared-nothing architecture makes sharing and consuming datasets with customers the same as querying and using your own tables without having to develop costly APIs to share data outside of the organization.

When we utilize the Snowflake data exchange, the costs are shared between the producer and the consumer. The producer obviously incurs charges related to producing that dataset within their own Snowflake account, and they will also pay the storage cost for that data as they would with any other table in their account. When consumers go to query data that has been shared with them, they are bringing their own compute resources to service those queries the same way they would for any other dataset within their Snowflake account. 

Why Snowflake?

Snowflake is a cloud-native data platform. When a company uses Snowflake, they are able to store and manage all of their data on one platform. The novel multi-clustered, shared-nothing architecture that made Snowflake stand out in the data-warehouse market also enables workloads like the data exchange. With the storage layer being completely isolated from the compute layer, provisioning access is easy, secure and performant. By making full use of the right data warehouse, organizations will become more data-driven and can position themselves for success in the future.  

Making a transition to a data-driven organization can be challenging, but luckily, we’re here to help. Sometimes, it may seem like it’s easiest for younger organizations (as in our recent case study with Electrify America), but it can be simple for more mature organizations as well. Message me on LinkedIn, or email us to see if Snowflake is right for you! 

More About the Author

Colin Murray

Data Lead
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