Collaborating with users in other Snowflake accounts involves setting up a process to share data and access privileges securely between different accounts. Snowflake is a cloud-based data warehousing platform that allows organizations to store, process, and analyze data. To collaborate between Snowflake accounts, you generally follow these steps:

1. Establish a Trust Relationship: To allow users in one Snowflake account to access objects (databases, schemas, tables, etc.) in another account, you need to establish a trust relationship between the accounts. This involves creating a trusted relationship from the "source" account to the "target" account, enabling users from the source account to authenticate into the target account.
2. Setup External Stage: An external stage is used to store files (like CSV, JSON, etc.) in cloud storage (like AWS S3 or Azure Blob Storage). You can create an external stage in your target account to reference data stored in your source account's cloud storage.
3. Grant Necessary Privileges: In the source account, grant the necessary privileges to allow users from the target account to access specific objects. This can include granting privileges on databases, schemas, tables, views, etc.
4. Create Virtual Warehouse (Optional): If you want users in the target account to execute queries in your source account, you can create a Virtual Warehouse (Snowflake's compute resource) in your target account.
5. Use Secure Views (Optional): To control the data being shared, you can create secure views in the source account. Secure views allow you to expose only specific columns or rows of data to users in the target account.
6. Authentication and Connection: Users in the target account will need to authenticate into the source account using Snowflake's federated authentication mechanisms. This might involve using Single Sign-On (SSO) or other authentication methods.
7. Execute Queries: Once the trust relationship is established, users from the target account can use their credentials to authenticate and then run queries against the objects in the source account, possibly using the external stage to access data.
8. Monitor and Audit: Ensure that you have proper monitoring and auditing mechanisms in place to track access and usage of shared data between accounts.

It's important to note that this process involves careful consideration of security, data privacy, and access control. Collaboration across Snowflake accounts should be planned and executed with a focus on maintaining the integrity of the data and complying with relevant regulations.

There are a few ways to collaborate with users in your own Snowflake account:

• Create a share: A share is a named Snowflake object that encapsulates all of the information required to share a database. You can create a share of a database and then grant access to specific objects in the database to other users in your account.
• Create a role: A role is a collection of privileges that can be granted to users. You can create a role that grants specific privileges to users who need to collaborate on data.
• Use workspaces: Workspaces are a way to group together related objects, such as databases, tables, and views. You can create a workspace and then invite other users to collaborate on the objects in the workspace.
• Use virtual private clouds (VPCs): VPCs are a way to isolate traffic between different users in your account. You can create a VPC and then invite other users to join the VPC.

Here are some additional things to keep in mind when collaborating with users in your own Snowflake account:

• Use strong passwords and MFA: It is important to use strong passwords and multi-factor authentication (MFA) to protect your account and data.
• Grant access carefully: Only grant users access to the data and objects that they need to access.
• Monitor activity: Monitor user activity to make sure that users are not accessing data or objects that they should not be accessing.
• Use encryption: Use encryption to protect your data.

By following these tips, you can collaborate with users in your own Snowflake account securely.

The data protection laws that apply to data sharing on Snowflake vary depending on the location of the data and the parties involved in the sharing.

In general, data protection laws require that organizations take steps to protect personal data from unauthorized access, use, disclosure, alteration, or destruction. These laws may also require organizations to obtain consent from individuals before sharing their personal data.

Some of the data protection laws that may apply to data sharing on Snowflake include:

• The General Data Protection Regulation (GDPR): The GDPR is a European Union law that applies to organizations that process personal data of individuals located in the European Union. The GDPR requires organizations to comply with a number of data protection requirements, including obtaining consent from individuals before sharing their personal data.
• The California Consumer Privacy Act (CCPA): The CCPA is a California law that applies to organizations that collect personal information of California residents. The CCPA gives California residents certain rights with respect to their personal information, including the right to request that organizations delete their personal information.
• The Personal Information Protection and Electronic Documents Act (PIPEDA): PIPEDA is a Canadian law that applies to organizations that collect personal information of individuals located in Canada. PIPEDA requires organizations to comply with a number of data protection requirements, including obtaining consent from individuals before sharing their personal data.

It is important to note that this is not an exhaustive list of the data protection laws that may apply to data sharing on Snowflake. Organizations should consult with legal counsel to determine which data protection laws apply to their specific situation.

Here are some additional tips for complying with data protection laws when sharing data on Snowflake:

• Identify the applicable data protection laws: The first step is to identify the applicable data protection laws. This will depend on the location of the data and the parties involved in the sharing.
• Obtain consent: If required by law, organizations should obtain consent from individuals before sharing their personal data. Consent should be obtained in a clear and unambiguous manner.
• Use appropriate safeguards: Organizations should use appropriate safeguards to protect personal data when sharing it on Snowflake. These safeguards may include encryption, access controls, and audit logs.
• Monitor compliance: Organizations should monitor their compliance with data protection laws on an ongoing basis. This includes reviewing their data sharing practices and making changes as needed.

Here are a few ways to track what actions have been performed on your shared data on Snowflake:

• Use the Snowflake audit log: The Snowflake audit log tracks all access to data in Snowflake, including data sharing. You can use the audit log to see who has accessed your shared data, when they accessed it, and what they did with it.The Snowflake audit log is a table that stores records of all data access events. These events include data sharing, data loading, data querying, and data updates.

  The audit log can be filtered by a number of criteria, such as user, object, and action. The audit log can also be exported to a file for further analysis.

• Use the Snowflake Data Access Governance (DAG) tool: The DAG tool provides a more granular view of data access than the audit log. The DAG tool allows you to see who has access to specific data objects, and what permissions they have to those objects.The DAG tool can be used to create data access policies that define who can access specific data objects and what permissions they have to those objects. The DAG tool can also be used to audit data access and to generate reports on data access.
• Use a third-party auditing tool: There are a number of third-party auditing tools that you can use to audit data sharing on Snowflake. These tools can provide additional features, such as data lineage and data masking.Data lineage is the tracking of the movement of data through your Snowflake environment. This can help you to identify the sources of your data and the downstream systems that use it.

  Data masking is a technique that can be used to obscure sensitive data before it is shared with partners. This can help to protect your data from unauthorized access and misuse.

By using one of these methods, you can help to ensure that your shared data is being accessed only by authorized users and that any actions performed on the data are being tracked.

Here are the steps on how to track what actions have been performed on your shared data using the Snowflake audit log:

1. Log in to your Snowflake account.
2. Click on the Administration tab.
3. Click on the Audit Log tile.
4. In the Filter section, select the Data Sharing event type.
5. In the Action section, select the action that you want to track.
6. Click on the Run button.
7. The audit log will display a list of all data sharing events that have occurred within the selected time range and that involve the selected action.
8. You can use the User, Object, Action, Timestamp, and Details columns to identify what actions have been performed on your shared data.

There are a few ways to track when your shared data has been accessed on Snowflake.

• Use the Snowflake audit log: The Snowflake audit log tracks all access to data in Snowflake, including data sharing. You can use the audit log to see who has accessed your shared data, when they accessed it, and what they did with it.

  The Snowflake audit log is a table that stores records of all data access events. These events include data sharing, data loading, data querying, and data updates.

  The audit log can be filtered by a number of criteria, such as user, object, and action. The audit log can also be exported to a file for further analysis.

• Use the Snowflake Data Access Governance (DAG) tool: The DAG tool provides a more granular view of data access than the audit log. The DAG tool allows you to see who has access to specific data objects, and what permissions they have to those objects.

  The DAG tool can be used to create data access policies that define who can access specific data objects and what permissions they have to those objects. The DAG tool can also be used to audit data access and to generate reports on data access.

• Use a third-party auditing tool: There are a number of third-party auditing tools that you can use to audit data sharing on Snowflake. These tools can provide additional features, such as data lineage and data masking.

  Data lineage is the tracking of the movement of data through your Snowflake environment. This can help you to identify the sources of your data and the downstream systems that use it.

  Data masking is a technique that can be used to obscure sensitive data before it is shared with partners. This can help to protect your data from unauthorized access and misuse.

By using one of these methods, you can help to ensure that your shared data is being accessed only by authorized users.

Here are the steps on how to track when your shared data has been accessed using the Snowflake audit log:

1. Log in to your Snowflake account.
2. Click on the Administration tab.
3. Click on the Audit Log tile.
4. In the Filter section, select the Data Sharing event type.
5. In the Time Range section, select the period of time that you want to track.
6. Click on the Run button.
7. The audit log will display a list of all data sharing events that have occurred within the selected time range.
8. You can use the User, Object, Action, and Timestamp columns to identify when your shared data has been accessed.

There are a few ways to track who has accessed your shared data on Snowflake.

• Use the Snowflake audit log: The Snowflake audit log tracks all access to data in Snowflake, including data sharing. You can use the audit log to see who has accessed your shared data, when they accessed it, and what they did with it.

  The Snowflake audit log is a table that stores records of all data access events. These events include data sharing, data loading, data querying, and data updates.

  The audit log can be filtered by a number of criteria, such as user, object, and action. The audit log can also be exported to a file for further analysis.

• Use the Snowflake Data Access Governance (DAG) tool: The DAG tool provides a more granular view of data access than the audit log. The DAG tool allows you to see who has access to specific data objects, and what permissions they have to those objects.

  The DAG tool can be used to create data access policies that define who can access specific data objects and what permissions they have to those objects. The DAG tool can also be used to audit data access and to generate reports on data access.

• Use a third-party auditing tool: There are a number of third-party auditing tools that you can use to audit data sharing on Snowflake. These tools can provide additional features, such as data lineage and data masking.

  Data lineage is the tracking of the movement of data through your Snowflake environment. This can help you to identify the sources of your data and the downstream systems that use it.

  Data masking is a technique that can be used to obscure sensitive data before it is shared with partners. This can help to protect your data from unauthorized access and misuse.

By using one of these methods, you can help to ensure that your shared data is being accessed only by authorized users.

Here are the steps on how to track who has accessed your shared data using the Snowflake audit log:

1. Log in to your Snowflake account.
2. Click on the Administration tab.
3. Click on the Audit Log tile.
4. In the Filter section, select the Data Sharing event type.
5. Click on the Run button.
6. The audit log will display a list of all data sharing events that have occurred in your account.
7. You can use the User, Object, and Action columns to identify who has accessed your shared data, when they accessed it, and what they did with it.

There are a few ways to audit data sharing on Snowflake.

• Use the Snowflake audit log: The Snowflake audit log tracks all access to data in Snowflake, including data sharing. You can use the audit log to see who has accessed your shared data, when they accessed it, and what they did with it.
• Use the Snowflake Data Access Governance (DAG) tool: The DAG tool provides a more granular view of data access than the audit log. You can use the DAG tool to see who has access to specific data objects, and what permissions they have to those objects.
• Use a third-party auditing tool: There are a number of third-party auditing tools that you can use to audit data sharing on Snowflake. These tools can provide additional features, such as data lineage and data masking.

By using one of these methods, you can help to ensure that your shared data is being accessed only by authorized users.

Here are some additional details about each of these methods:

• Snowflake audit log: The Snowflake audit log tracks all access to data in Snowflake, including data sharing. The audit log is stored in a separate database, so it is not affected by changes to your data.

  You can use the audit log to see who has accessed your shared data, when they accessed it, and what they did with it. The audit log can be filtered by a number of criteria, such as user, object, and action.

• Snowflake Data Access Governance (DAG) tool: The DAG tool provides a more granular view of data access than the audit log. The DAG tool allows you to see who has access to specific data objects, and what permissions they have to those objects.

  You can use the DAG tool to create data access policies that define who can access specific data objects and what permissions they have to those objects. The DAG tool can also be used to audit data access and to generate reports on data access.

• Third-party auditing tool: There are a number of third-party auditing tools that you can use to audit data sharing on Snowflake. These tools can provide additional features, such as data lineage and data masking.

  Data lineage is the tracking of the movement of data through your Snowflake environment. This can help you to identify the sources of your data and the downstream systems that use it.

  Data masking is a technique that can be used to obscure sensitive data before it is shared with partners. This can help to protect your data from unauthorized access and misuse.

By using one of these methods, you can help to ensure that your shared data is being accessed only by authorized users.

There are a few ways to encrypt your shared data on Snowflake.

• Use Secure Data Sharing (SDS): SDS encrypts all shared data in transit and at rest. This helps to protect your data from unauthorized access.
• Use customer-managed keys: Customer-managed keys (CMKs) allow you to encrypt your data with your own encryption keys. This can give you more control over your data encryption.
• Use a third-party encryption solution: There are a number of third-party encryption solutions that you can use to encrypt your data. These solutions can provide additional encryption features, such as key rotation and key management.

By using SDS, CMKs, or a third-party encryption solution, you can help to protect your shared data from unauthorized access.

Here are some additional details about each of these methods:

• Secure Data Sharing (SDS): SDS encrypts all shared data in transit and at rest. This helps to protect your data from unauthorized access.

  When you share data with another account using SDS, the data is encrypted using a key that is managed by Snowflake. This ensures that the data is protected from unauthorized access even if the shared object is compromised.

  SDS also encrypts the data in transit between your account and the account that you are sharing the data with. This helps to protect the data from unauthorized access while it is being transferred.

• Customer-managed keys: Customer-managed keys (CMKs) allow you to encrypt your data with your own encryption keys. This can give you more control over your data encryption.

  When you use CMKs, you create a key pair in Snowflake and then store the private key in a secure location. You then use the public key to encrypt your data.

  When you share data with another account using CMKs, you share the public key with the account. The account can then use the public key to decrypt the data.

• Third-party encryption solution: There are a number of third-party encryption solutions that you can use to encrypt your data. These solutions can provide additional encryption features, such as key rotation and key management.

  When you use a third-party encryption solution, you will need to create an account with the solution provider and then configure the solution to encrypt your data.

  Once your data is encrypted, you can share it with other accounts by using the solution provider's API or SDK.

By using SDS, CMKs, or a third-party encryption solution, you can help to protect your shared data from unauthorized access.

There are a few ways to control who has access to your shared data on Snowflake.

• Use roles: Roles are a way to group together permissions. You can create roles that give users specific permissions to your shared data. For example, you could create a role that gives users permission to SELECT data from your shared tables.
• Use grants: Grants are a way to give users specific permissions to specific objects. For example, you could grant a user permission to SELECT data from the customers table in your shared database.
• Use data masking: Data masking is a technique that can be used to obscure sensitive data before it is shared with partners. This can help to protect your data from unauthorized access and misuse.

By using roles, grants, and data masking, you can control who has access to your shared data and what they can do with it.

Here are some additional details about each of these methods:

• Roles: Roles are a powerful way to control access to your data. When you create a role, you can specify the permissions that the role grants. You can then assign the role to users or groups.

  For example, you could create a role called data_analyst that grants users permission to SELECT data from all tables in your shared database. You could then assign the data_analyst role to all of your data analysts.

• Grants: Grants are a more granular way to control access to your data. When you grant a user permission to an object, you are specifying exactly what the user can do with the object.

  For example, you could grant a user permission to SELECT data from the customers table in your shared database. You could also grant the user permission to INSERT, UPDATE, or DELETE data from the table.

• Data masking: Data masking is a technique that can be used to obscure sensitive data before it is shared with partners. This can help to protect your data from unauthorized access and misuse.

  There are a number of different ways to mask data. One common approach is to replace sensitive data with a placeholder value, such as "X" or "*****". Another approach is to scramble the data so that it is no longer readable.

  Data masking can be applied to individual columns or to entire tables. It can also be applied to data in transit or at rest.

By using roles, grants, and data masking, you can control who has access to your shared data and what they can do with it. This will help to protect your data from unauthorized access and misuse.

Snowflake offers a number of security features to help you share data securely with your partners. These features include:

• Secure Data Sharing (SDS): SDS is a powerful tool that allows you to share selected objects in a database in your account with other Snowflake accounts. SDS provides a number of security features, including:
  • Fine-grained access control: You can control who has access to your shared data, and what actions they can perform on it.
  • Audit logging: All access to shared data is logged, so you can track who has accessed your data and what they have done with it.
  • Data encryption: All shared data is encrypted in transit and at rest, so it is protected from unauthorized access.
• Data masking: Data masking is a technique that can be used to obscure sensitive data before it is shared with partners. This can help to protect your data from unauthorized access and misuse.
• Data governance: Snowflake offers a number of data governance features that can help you to manage your data more effectively. These features can help you to ensure that your data is accurate, complete, and compliant with regulations.

By using the security features available on Snowflake, you can help to ensure that your data is shared securely with your partners.

Here are some additional details about each of these security features:

• Secure Data Sharing (SDS): SDS allows you to share selected objects in a database in your account with other Snowflake accounts. The objects that you can share include tables, views, materialized views, and user-defined functions (UDFs).

  When you share an object with another account, you can control who has access to the object and what actions they can perform on it. You can also specify whether the object is shared with the entire account or with a specific user or group.

  SDS provides a number of audit logs that track all access to shared objects. These logs can help you to identify who has accessed your data and what they have done with it.

  SDS also encrypts all shared data in transit and at rest. This helps to protect your data from unauthorized access.

• Data masking: Data masking is a technique that can be used to obscure sensitive data before it is shared with partners. This can help to protect your data from unauthorized access and misuse.

  There are a number of different ways to mask data. One common approach is to replace sensitive data with a placeholder value, such as "X" or "*****". Another approach is to scramble the data so that it is no longer readable.

  Data masking can be applied to individual columns or to entire tables. It can also be applied to data in transit or at rest.

• Data governance: Snowflake offers a number of data governance features that can help you to manage your data more effectively. These features can help you to ensure that your data is accurate, complete, and compliant with regulations.

  Some of the data governance features available on Snowflake include:

  • Data lineage: Data lineage tracks the movement of data through your Snowflake environment. This can help you to identify the sources of your data and the downstream systems that use it.
  • Data quality: Data quality tools can help you to identify and correct errors in your data.
  • Data compliance: Data compliance tools can help you to ensure that your data is compliant with regulations.

By using the security features available on Snowflake, you can help to ensure that your data is shared securely with your partners and that it is managed effectively.

There are many ways to share data with partners. The best way for you will depend on the specific needs of your business and your partners. Here are a few common methods:

• Direct file transfer: This is the simplest way to share data, but it can be insecure if not done properly. To protect your data, you can use a secure file transfer protocol (SFTP) or a cloud-based file sharing service.
• API integration: This is a more secure way to share data, as it allows your partners to access your data directly through an application programming interface (API). This can be a good option if you need to share large amounts of data or if you need your partners to be able to access your data in real time.
• Data mart: A data mart is a repository of data that is specifically designed for sharing with partners. This can be a good option if you need to share a large amount of data with a large number of partners.
• Data broker: A data broker is a third-party company that specializes in facilitating data sharing between businesses. This can be a good option if you need to share data with partners that you do not have a direct relationship with.

No matter which method you choose, it is important to have a clear agreement with your partners about how the data will be used. This agreement should include details about the types of data that will be shared, how the data will be protected, and how the data will be used.

Here are some additional tips for sharing data with partners:

• Use encryption: To protect your data from unauthorized access, you should always use encryption when sharing data with partners.
• Limit access: Only give your partners access to the data that they need. This will help to reduce the risk of data breaches.
• Monitor usage: Monitor how your partners are using your data. This will help you to ensure that they are using it in accordance with the agreement.
• Review the agreement regularly: As your business needs change, you may need to update your agreement with your partners. Review the agreement regularly to make sure that it is still meeting your needs.

By following these tips, you can help to ensure that your data is shared securely and responsibly with your partners.

Snowflake's integration with other tools and platforms can be used to support DevOps in a number of ways:

• Automate data pipelines: Snowflake can be integrated with a variety of data integration tools, such as Informatica and Talend, to automate data pipelines. This can help to reduce the manual work involved in data integration and free up developers to focus on other tasks.
• Deploy applications faster: Snowflake can be integrated with a variety of continuous integration and continuous delivery (CI/CD) tools, such as Jenkins and Bamboo, to help developers deploy applications faster. This can help to shorten the time to market for new applications and improve the agility of the development team.
• Monitor applications: Snowflake can be integrated with a variety of monitoring tools, such as New Relic and AppDynamics, to help developers monitor applications. This can help to identify and troubleshoot performance problems quickly and easily.
• Test applications: Snowflake can be integrated with a variety of testing tools, such as Selenium and JUnit, to help developers test applications. This can help to ensure that applications are working as expected before they are deployed to production.
• Secure applications: Snowflake can be integrated with a variety of security tools, such as Cloudera Ranger and IBM Security Identity Manager, to help developers secure applications. This can help to protect applications from unauthorized access and malicious attacks.

By integrating Snowflake with other tools and platforms, DevOps teams can automate tasks, deploy applications faster, monitor applications, test applications, and secure applications. This can help to improve the efficiency, agility, and security of the development process.

Here are some specific examples of how Snowflake can be integrated with other tools and platforms to support DevOps:

• Automate data pipelines: Snowflake can be integrated with Informatica to automate data pipelines. Informatica is a data integration tool that can help to move data from a variety of sources into Snowflake. Once the data is in Snowflake, it can be used to build data models and create reports.
• Deploy applications faster: Snowflake can be integrated with Jenkins to help deploy applications faster. Jenkins is a CI/CD tool that can help to automate the build, test, and deployment of applications. By integrating Snowflake with Jenkins, developers can automate the process of loading data into Snowflake and then deploying applications that use the data.
• Monitor applications: Snowflake can be integrated with New Relic to help monitor applications. New Relic is a monitoring tool that can help to collect metrics and logs from applications. By integrating Snowflake with New Relic, developers can monitor the performance of applications that use the data in Snowflake.
• Test applications: Snowflake can be integrated with Selenium to help test applications. Selenium is a testing tool that can help to automate the testing of web applications. By integrating Snowflake with Selenium, developers can automate the testing of applications that use the data in Snowflake.
• Secure applications: Snowflake can be integrated with Cloudera Ranger to help secure applications. Cloudera Ranger is a security tool that can help to manage access to data in Snowflake. By integrating Snowflake with Cloudera Ranger, developers can ensure that only authorized users can access the data in Snowflake.

By integrating Snowflake with other tools and platforms, DevOps teams can automate tasks, deploy applications faster, monitor applications, test applications, and secure applications. This can help to improve the efficiency, agility, and security of the development process.

There are a number of ways to share data with external systems:

• **Export data: You can export data from Snowflake to a variety of file formats, such as CSV, JSON, and XML. You can then import the data into the external system.
• **Use an API: Snowflake offers a REST API that you can use to programmatically share data with external systems.
• **Use a data integration tool: There are a number of data integration tools that can help you to share data between Snowflake and external systems. These tools can help you to move data, transform data, and load data into external systems.
• **Use a data warehouse appliance: A data warehouse appliance is a pre-built solution that can help you to share data between Snowflake and external systems. These appliances can offer a variety of features, such as data encryption, data compression, and data replication.

Here are some additional things to keep in mind when sharing data with external systems:

• Consider the security implications of sharing data with external systems. You will need to ensure that the data is encrypted and that it is only accessible to authorized users.
• Consider the performance implications of sharing data with external systems. You will need to ensure that the data can be transferred to the external system in a timely manner.
• Consider the compatibility of the external system with Snowflake. You will need to ensure that the external system can read and write the data in the format that Snowflake uses.

By following these tips, you can easily share data with external systems.

Here are some specific examples of how you can share data with external systems using the methods mentioned above:

• Export data: You can export data from Snowflake to a CSV file and then import the file into a spreadsheet application.
• Use an API: You can use the Snowflake REST API to programmatically share data with a web application.
• Use a data integration tool: You can use a data integration tool, such as Informatica or Talend, to move data from Snowflake to a data warehouse.
• Use a data warehouse appliance: You can use a data warehouse appliance, such as IBM Netezza or Greenplum, to share data between Snowflake and other data sources.

By using these methods, you can easily share data with external systems and gain insights from your data.

There are two ways to share data with users who do not have a Snowflake account:

1. Create a reader account: A reader account is a way to share data with users who do not have a Snowflake account. Reader accounts give users read-only access to shared data, without requiring them to become Snowflake customers.
2. Use a data sharing partner: There are a number of data sharing partners that can help you to share data with users who do not have a Snowflake account. Data sharing partners can provide a variety of services, such as data hosting, data encryption, and data tokenization.

Here are the steps on how to create a reader account:

1. Sign in to Snowsight.
2. In the navigation menu, select Data » Private Sharing.
3. Select Share » Create a Reader Account.
4. In the Create Reader Account dialog, specify the following information:
   • Username: The username for the reader account.
   • Password: The password for the reader account.
   • Email address: The email address for the reader account.
   • Permissions: The permissions that you want to grant to the reader account.
5. Click Create.

Once you have created a reader account, the user will be able to access the data that you shared, subject to the permissions that you granted.

Here are some additional things to keep in mind when sharing data with users who do not have a Snowflake account:

• You can only share data with users who have been granted the ACCOUNTADMIN role or the CREATE ACCOUNT global privilege.
• You can share data with users in any region.
• You can revoke access to shared data at any time.

By following these steps, you can easily share data with users who do not have a Snowflake account.

Here are some data sharing partners that you can consider:

• Fivetran: Fivetran is a data integration platform that can help you to move data from a variety of sources into Snowflake. Fivetran can also help you to share data with users who do not have a Snowflake account.
• Informatica: Informatica is another data integration platform that can help you to move data from a variety of sources into Snowflake. Informatica can also help you to share data with users who do not have a Snowflake account.
• Snowflake Data Sharing: Snowflake offers a Data Sharing service that can help you to share data with users who do not have a Snowflake account. Snowflake Data Sharing can provide a variety of services, such as data hosting, data encryption, and data tokenization.

By using a data sharing partner, you can easily share data with users who do not have a Snowflake account.

There are two ways to share data with users in other Snowflake accounts:

1. Create a data exchange: A data exchange is a way to share data with a group of accounts that you invite. To create a data exchange, you need to specify the data that you want to share, the permissions that you want to grant to the accounts, and the terms of the data sharing agreement.
2. Create a listing: A listing is a data product that you can offer to one or more accounts. Listings can include additional metadata about the data, such as a description, usage statistics, and tags. You can also make listings public, so that they can be discovered and consumed by any Snowflake account.

Here are the steps on how to create a data exchange:

1. Sign in to Snowsight.
2. In the navigation menu, select Data » Data Exchanges.
3. Select Create Data Exchange.
4. In the Create Data Exchange dialog, specify the following information:
   • Data: The data that you want to share.
   • Permissions: The permissions that you want to grant to the accounts.
   • Terms of agreement: The terms of the data sharing agreement.
5. Click Create.

Once you have created a data exchange, you can invite other accounts to join the data exchange. The invited accounts will be able to access the data that you shared, subject to the permissions that you granted.

Here are the steps on how to create a listing:

1. Sign in to Snowsight.
2. In the navigation menu, select Data » Listings.
3. Select Create Listing.
4. In the Create Listing dialog, specify the following information:
   • Data: The data that you want to share.
   • Description: A description of the data.
   • Usage statistics: Usage statistics for the data.
   • Tags: Tags for the data.
5. Click Create.

Once you have created a listing, you can make it public or private. Public listings can be discovered and consumed by any Snowflake account. Private listings can only be accessed by accounts that you have granted access to.

Here are some additional things to keep in mind when sharing data with users in other Snowflake accounts:

• You can only share data with accounts that have been granted the ACCOUNTADMIN role or the CREATE ACCOUNT global privilege.
• You can share data with accounts that are in the same region or in different regions.
• You can revoke access to shared data at any time.

By following these steps, you can easily share data with users in other Snowflake accounts.

There are two ways to share data with users in your own Snowflake account:

Create a direct share: A direct share is a way to share specific database objects with another user in your account. To create a direct share, you need to specify the user that you want to share the data with, the database objects that you want to share, and the permissions that you want to grant the user.

Create a secure view: A secure view is a way to share data with another user without giving them direct access to the underlying data. To create a secure view, you need to specify the data that you want to share, the filters that you want to apply to the data, and the permissions that you want to grant the user.

Here are the steps on how to create a direct share:

1. Sign in to Snowsight.
2. In the navigation menu, select Data » Private Sharing.
3. Select Share » Create a Direct Share.
4. In the Share Data dialog, specify the following information:
User: The user that you want to share the data with.
Database objects: The database objects that you want to share.
Permissions: The permissions that you want to grant the user.
5. Click Share.

Here are the steps on how to create a secure view:

1. Sign in to Snowsight.
2. In the navigation menu, select Data » Private Sharing.
3. Select Share » Create a Secure View.
4. In the Share Data dialog, specify the following information:
Data: The data that you want to share.
Filters: The filters that you want to apply to the data.
Permissions: The permissions that you want to grant the user.
5. Click Share.

Once you have created a direct share or a secure view, the user that you shared the data with will be able to access the data in the specified database objects. The user's permissions will determine what they can do with the data.

Here are some additional things to keep in mind when sharing data with users in your own Snowflake account:

- You can only share data with users who have been granted the ACCOUNTADMIN role or the CREATE ACCOUNT global privilege.
- You can share data with users in other accounts by creating a data exchange.
- You can revoke access to shared data at any time.

By following these steps, you can easily share data with users in your own Snowflake account.

The legal and regulatory requirements for data sharing on Snowflake will vary depending on the jurisdiction in which you are located. However, there are some general principles that you should follow to ensure that your data sharing practices are compliant with applicable laws and regulations.

- Obtain consent from the data subjects: In most cases, you will need to obtain consent from the data subjects before you can share their data with third parties. This consent should be specific, informed, and freely given.

- Only share data that is necessary for the intended purpose: You should only share data that is necessary for the intended purpose of the sharing. For example, if you are sharing data with a third party to conduct research, you should only share the data that is necessary for the research.

- Protect the confidentiality of the data: You should take steps to protect the confidentiality of the data that you share. This may include encrypting the data, using secure transmission methods, and limiting access to the data to authorized individuals.

- Comply with applicable laws and regulations: You should comply with all applicable laws and regulations when sharing data on Snowflake. This may include laws governing data privacy, data security, and data transfer.

By following these principles, you can help to ensure that your data sharing practices are compliant with applicable laws and regulations.

Here are some additional tips for complying with legal and regulatory requirements for data sharing on Snowflake:

- **Consult with legal counsel:** If you are unsure about the legal and regulatory requirements for data sharing in your jurisdiction, you should consult with legal counsel.

- Develop data sharing policies and procedures: You should develop data sharing policies and procedures that are tailored to your specific needs. These policies and procedures should be documented and should be made available to all employees who are involved in data sharing.

- Conduct regular training: You should conduct regular training for employees who are involved in data sharing. This training should cover the legal and regulatory requirements for data sharing, as well as the company's data sharing policies and procedures.

- Monitor data sharing activity: You should monitor data sharing activity to ensure that it is compliant with applicable laws and regulations. This monitoring may include reviewing audit logs, reviewing data sharing usage reports, and conducting spot checks.

By following these tips, you can help to ensure that your data sharing practices are compliant with applicable laws and regulations.

There are a few ways to track data sharing on Snowflake:

- Use the Snowflake audit logs: The Snowflake audit logs track all data access activity, including data sharing. You can use the audit logs to track who has accessed shared data, when they accessed it, and what they did with it.

- **Use the Snowflake Data Sharing Usage views:** The Snowflake Data Sharing Usage views provide information about the usage of shared data, such as the number of queries that have been run against shared data, the amount of data that has been accessed, and the time that has been spent accessing shared data.

- Use the Snowflake Data Sharing API: The Snowflake Data Sharing API can be used to programmatically track data sharing. You can use the API to get information about shared data, such as the list of accounts that have been granted access to shared data, the permissions that have been granted to each account, and the usage of shared data by each account.

By tracking data sharing, you can gain insights into how your data is being used and identify any potential security risks.

Here are some additional tips for tracking data sharing on Snowflake:

- Set up alerts: You can set up alerts in Snowflake to notify you when there is suspicious data sharing activity. This can help you to quickly identify and investigate any potential security risks.

- Review the audit logs regularly: It is important to review the audit logs regularly to track data sharing activity. This will help you to identify any unauthorized data access or usage.

- Use the Data Sharing Usage views: The Snowflake Data Sharing Usage views can provide you with insights into how your data is being used. This information can be helpful in identifying potential security risks.

- Use the Data Sharing API: The Snowflake Data Sharing API can be used to programmatically track data sharing. This can be helpful if you need to track data sharing at scale or if you need to integrate data sharing tracking with other systems.

By following these tips, you can help to ensure that your data sharing activity is tracked and monitored effectively.

There are a number of ways to secure data sharing on Snowflake:

- Use strong passwords and MFA: When creating accounts and granting access to data, use strong passwords and enable multi-factor authentication (MFA) to help protect against unauthorized access.

- Grant access only to the data that is needed: When sharing data, grant access only to the specific objects that are needed, and use the least privilege principle to ensure that users only have the permissions they need to perform their jobs.

- Use secure views: Secure views can be used to share data with users without giving them access to the underlying data. Secure views can be configured to only return certain columns or rows of data, or to apply filters or transformations to the data before it is returned.

- Encrypt data in transit and at rest: Snowflake supports encryption of data in transit and at rest to help protect data from unauthorized access.

- Monitor data access: Use Snowflake's auditing and monitoring features to track data access and identify any unauthorized activity.

- Use data governance policies: Data governance policies can be used to define and enforce rules for data sharing. Data governance policies can help to ensure that data is shared in a compliant and secure manner.

By following these best practices, you can help to secure data sharing on Snowflake and protect your sensitive data.

Here are some additional tips for securing data sharing on Snowflake:

- Use data masking: Data masking can be used to obscure sensitive data before it is shared. This can help to protect sensitive data from unauthorized access and malicious attacks.

- Use data pseudonymization: Data pseudonymization can be used to replace sensitive data with non-sensitive data. This can help to protect sensitive data from unauthorized access and malicious attacks, while still allowing the data to be used for analysis and reporting.

- Use data encryption: Data encryption can be used to protect data from unauthorized access and malicious attacks. Snowflake supports a variety of encryption algorithms, including AES-256 and RSA-2048.

- Use data access controls: Data access controls can be used to restrict access to data to authorized users. Snowflake supports a variety of data access controls, including role-based access control (RBAC) and fine-grained access control (FGAC).

By following these tips, you can help to secure data sharing on Snowflake and protect your sensitive data.