When using the cloud-based softwares together though, enterprise businesses have the complete infrastructure to store, manage, activate and report on data with ease.
Free Data Cloud 101 Guide
By the end of ‘Salesforce Data Cloud 101’ you’ll understand exactly what the software does and how it empowers business activities with real-time data about your customers.
Introduction to CDPs
Example use cases
Getting started with Data Cloud
Data Cloud features
Preparing your account
Tips & best practices
Download now
3D eBook cover with text Salesforce Data Cloud 101: Mastering Your Customer Data Platform
The Salesforce to Snowflake integration
For years, a native database integration for Snowflake and Salesforce has made it possible for users to connect their platforms quickly and seamlessly.
Snowflake Connector - importing Snowflake data into CRM Analytics.
Snowflake Output Connector - pushing data into country code of nepal your Snowflake data warehouse.
Snowflake Direct Connector - live access to Snowflake data from Salesforce.
Third-Party Connectors to Snowflake - supports syncing and moving data between Salesforce, Snowflake and third-party cloud applications.
Historically, the data has been copied from Snowflake to Salesforce and vice versa, in scheduled batches.
As part of the Salesforce Winter ’24 release, Salesforce announced their new Data Share feature. Instead of copying the data, it is ‘shared’ between Snowflake and Salesforce Data Cloud with Zero ETL (Extract Transform Load). This eliminates drawbacks such as query time and delayed data syncing, and makes using and analysing the data instant.
In a nutshell, the integration allows users and AI features like Einstein, real-time access to data. Once the upcoming Bring-Your-Own-Lake (BYOL) Data Federation launches, this will be fully bi-directional.
Use cases for Salesforce Data Cloud & Snowflake
Obviously with a breadth of data available to businesses of all industries, the use cases for combining Data Cloud and Snowflake are endless. A few of the most obvious are:
Using transactional customer data in Data Cloud alongside product data collected via POS or ecommerce platform and stored in Snowflake. Gaining insights about purchase behaviour and product categories to inform both reporting and machine-learning.
Analysing Sales Cloud data stored in Data Cloud with third-party data found in ‘The Snowflake Marketplace’; a resource for users containing live data sets from third-party providers. The combination of first and third party data can inform strategies, sales tactics, and ultimately deliver more sales and revenue.
Reviewing advanced website data in Snowflake with customer data points in Data Cloud to run informed, sophisticated and AI-driven segmentation and achieve better marketing conversion rates.
Hopefully, what this blog article has made clear is that it’s not ‘Salesforce Data Cloud vs Snowflake’ but ‘Salesforce Data Cloud and Snowflake’!
As complementary softwares that can really take data warehousing and activation to the next level, any ambitious business should be exploring their options for both.
If you’d like to have a chat about Salesforce Data Cloud or how to integrate and use this with Snowflake, get in touch. We have data scientists and certified Salesforce developers available and ready to help!
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Anton Minnion
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