Salesforce and Snowflake Collaborate to Provide Bring Your Own Lake Data Sharing

Salesforce is offering the general availability of Bring Your Own Lake (BYOL) Data Sharing with the Snowflake Data Cloud from Salesforce Data Cloud. This builds on Salesforce and Snowflake’s existing partnership to bring together data storage and actionable insights for their customers, according to the companies.

Salesforce Data Cloud is a hyperscale customer data platform that lets companies unify all their Salesforce data with vast amounts of engagement data from external sources to create harmonized and unified customer profiles. It enables businesses to quickly action data across the Salesforce Customer 360 with AI, automation, and analytics across sales, service, marketing, and commerce applications, according to the company.

The collaboration bridges Salesforce and Snowflake data, solving a common challenge faced by businesses: the need to seamlessly combine customer data from Salesforce with data in Snowflake.

By doing so, companies can gain deeper insights into customer behavior, market trends, and operational efficiency—allowing them to react more swiftly to market changes, anticipate customer needs, and optimize their operations, according to the companies.

With Salesforce’s BYOL Data Sharing with the Snowflake Data Cloud, joint customers can enhance the value of their Salesforce data by combining it with enterprise data in Snowflake. Organizations can now power their Snowflake workloads with valuable customer data and insights from Salesforce Data Cloud.

This integration makes it easy to convert data into insights. In the coming months, Salesforce and Snowflake plan to launch BYOL Data Federation so Snowflake data can be accessed within Salesforce Data Cloud, completing the bidirectional data sharing capability.

Once unified, data accessed in Salesforce Data Cloud becomes natively available throughout existing applications and processes within the Customer 360.

BYOL Data Sharing with Snowflake opens up new possibilities across roles. For example:

  • A data scientist can build AI and machine learning models in Snowflake to determine customer purchase propensity scores for specific product categories. By joining Salesforce objects like profiles, website visits, and POS Data with Snowflake’s product category data, they can unlock new insights.
  • A marketer can enhance segmentation and personalize campaigns by merging CRM and non-CRM data. They can then use that data in custom AI models to predict customer preferences, leading to hyper-targeted campaigns and maximized engagement.
  • A salesperson can leverage intelligent forecasting and performance analytics by integrating CRM and third-party data in Snowflake. They can then refine strategies, optimize performance, and prioritize customer-centric success.
  • An analyst can drive informed decision-making by merging historical sales and contact data from Salesforce with web analytics data in Snowflake. This will help identify customer trends and behavior for strategic insights.

“With the Snowflake and Salesforce integration, we are enabling enterprises to experience a unified and frictionless modern data stack, so they can focus on delivering differentiated experiences for customers. “There is no AI without data, and together, we are well positioned to lead our customers through the growing interest in AI/ML,” said Christian Kleinerman, SVP of product at Snowflake.

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