Snowflake Adds Salesforce Integrations and More Building Blocks to Enable Your Data Cloud

 June 9, 2020 | Article   Muthulakshmi Sengottuvel

On June 2, 2020, Snowflake unveiled its first installment of native integrations with Salesforce and many new features designed to achieve full data mobility. The integrations make it easier for customers to access and analyze data in Snowflake and visualize it in Salesforce.

This announcement comes in the wake of Salesforce Ventures’ investment in Snowflake’s Series G funding round in February 2020 and a strategic partnership between the two parties aimed at digital transformation for joint customers.

The product integrations linking the two vendors’ cloud systems are:

  • Einstein Analytics Output Connector for Snowflake

It facilitates joint customers to move their data from Salesforce into Snowflake seamlessly. It also allows native access to Salesforce data, including automatic updates, enabling customers to consolidate their enterprise data in Snowflake and be up-to-date. The connector will be available for customers later this year.

  • Einstein Analytics Direct Data for Snowflake

It allows Einstein Analytics users to directly query not only Salesforce data residing in Snowflake but also data generated from their business applications, mobile apps, web activity, IoT devices, and acquired data from the Snowflake Data Marketplace. The Direct Data integration is currently available for any Einstein Analytics customer in open beta. It will be generally available for all customers later this year.

Snowflake also launched the Data Cloud, an ecosystem for Snowflake customers, partners, data providers, and data service providers to aggregate data. Snowflake believes that organizations will move their data siloed in cloud-based repositories and on-premises data centers to its platform. Data Cloud enables its customers to operate seamlessly across different cloud providers and their regions in a secured and governed manner.

New features for Snowflake Cloud Data Platform include:

  • Snowsight It is a new streamlined analyst experience within Snowflake that includes collaboration, visualization, and dashboards.
  • Dynamic Data Masking Create masking policies for data based on user permissions.
  • External Tokenization – Integrate with third-party token solutions for increased data protection.
  • Search Optimization Service Improve point lookup query performance on large data tables.
  • External Functions – Use Snowflake to call external services for query support and to build data pipelines that integrate with external libraries or services.
  • Java UDFs – Utilize Snowflake to run business logic developed in Java.
  • Organizations – Provision, operate, and manage multiple Snowflake accounts across various clouds.
  • Data Exchange – Create your data exchange to share live, governed data securely with customers, units, partners, and suppliers.
  • Snowflake Data Marketplace – Access and query third-party data sets from your Snowflake account.

According to Snowflake’s Senior Vice President of Product, Christian Kleinerman, the feature enhancements will help companies unify, integrate, analyze, and share virtually any amount of data, eliminating the complexity and friction of alternative solutions. Snowflake’s new product innovations will reduce data gaps, make actionable insights readily accessible to all business users, and provide richer data-driven user experiences.

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