Author: Nikhil Pai J
Snowflake provides its users with various ways to share their data with different Snowflake or non-Snowflake users. The challenge here would be to identify the right sharing feature that best suits your requirements. This blog gives you an overview of a few use cases where each of the data-sharing offerings could be best utilized.
When to use Snowflake’s Secure Direct Data Share?
A Direct Data Share is the simplest way of sharing data and can be used in various situations.
If the data producer knows the consumer and is in the same cloud and region, you can use direct data sharing.
If data consumers do not want to purchase a snowflake license, they can use direct data sharing to share data with their reader account.
If the Interaction between the Snowflake users for sharing data is normally “1 to 1,” where one is a provider and the other a consumer.
When monetization is not primarily considered the main focus.
Scenario 1:
When your dev/test and production environments are on different Snowflake accounts, and you do not want to use database replication, you might need your production data to test the new features/code introduced.
You can Share your production data with the dev/test account via a direct share.
Scenario 2:
When you want to share your data with a Business user who is neither using a Snowflake account nor any visualization tool to have an approval/review.
You can share your data using a Reader account so that you have full control and data is secure as Reader account users cannot perform any operation other than 'Read.’
When to use Snowflake's Private Data Exchange?
Snowflake’s Private Data Exchange can be used to
Improve operational efficiency by eliminating internal data silos
Opening up monetization opportunities by exchanging data with external organizations & improving collaboration.
Reduce data analysis costs when searching for new sources of external data.
Create new revenue streams by sharing data externally and monetizing the data assets at scale, etc.
A couple of scenarios are listed below.
Scenario 1:
The Snowflake Data Exchange can be leveraged to exchange data between different Snowflake users to securely collaborate with external parties such as vendors, suppliers, partners, and customers. Sharing of confidential/private data between different parties who have an agreement can be done using the Snowflake data exchange.
Scenario 2:
To break down data silos and reduce the time to market. Multiple datasets can be shared at a scale between business units or subsidiaries within the organization to break down data silos. Interchanging data with third-party vendors to help enrich internal datasets and to find and consume data on the other Data Exchanges to get business insights.
When to use Snowflake's Data Marketplace?
The Data Marketplace contains a wide range of data assets that are readily available to consume. They can be leveraged to
Enrich existing data by utilizing the data sets available on the marketplace.
Monetize your data assets by listing them on the marketplace.
Discover third-party data assets that can be utilized to get better insights.
Access fresh and live data at a moment's notice.
Reduce costs associated with sourcing and preparing the data.
Scenario 1:
Identifying seasonality trends by enriching existing Tours & Travels data with weather data available on the Marketplace.
Scenario 2:
Listing your organization’s existing Operational data, for example, transaction records and sensor logs, or Marketing data, for example, aggregated or de-identified customer information, preferences, web traffic, and so on, to the marketplace to monetize them.
Summary
Each Data sharing feature that Snowflake offers has its own set of advantages. There is no one way of sharing data using a specific feature since the use case could be unique in its own way. Depending on the scenarios and how well a data-sharing feature matches your requirements will be the deciding factor when choosing the right data-sharing feature.