Salesforce Data Cloud has been generating significant buzz, particularly with the introduction of a free tier for customers using the Enterprise and Unlimited editions. As Data Cloud evolves, many organizations are asking: how does it compare to data warehouse solutions like Snowflake, and why should we consider integrating Salesforce Data Cloud with Snowflake? Let’s explore what Salesforce Data Cloud and Snowflake offer and how integrating them can complement your existing data solutions.
What is Salesforce Data Cloud?
Originally launched as Salesforce Marketing Cloud’s Customer Data Platform (CDP), Data Cloud has since evolved into a comprehensive data platform. It ingests, harmonizes, and unifies data against customer profiles, driving insights as well as marketing segmentation and activation.
Although Data Cloud has capabilities similar to a Data Lake, it is not a replacement for data warehouse solutions like Snowflake. Instead, Data Cloud serves as an ideal companion to Snowflake for organizations looking to integrate their data warehouse data with CRM data in Salesforce, facilitating segmentation and activation through Marketing Cloud.
What is Snowflake?
Snowflake is a cloud-native data warehouse that offers scalable compute models for processing high data volumes on demand and storing large data volumes encrypted at rest, ensuring efficient performance and secured storage management. Snowflake can be deployed on Amazon AWS, Microsoft Azure, or Google Cloud, eliminating egress costs if you’re already using one of these providers.
Snowflake also features native data sharing through a Zero-Copy architecture, allowing users to share data across multiple organizations via Snowflake’s built-in Marketplace without the need for costly and complex data duplication.
Why You Should Integrate Data Cloud and Snowflake
Data Cloud natively supports Snowflake’s powerful Zero-Copy architecture. If you’re already leveraging Snowflake, integrating your data into Salesforce is straightforward. Simply set up the appropriate credentials and connect Salesforce to your Snowflake account. Data Cloud can then import tables and views without consuming additional storage or processing credits. Data Cloud credits are used for row access and sharing at a lower rate than for ingestion, and Snowflake views can filter data at the source to reduce volume.
Once data sharing is configured between Snowflake and Data Cloud, you can map data from Snowflake into Data Cloud’s individual data model, benefiting from Data Cloud’s identity resolution and harmonization features. This allows you to build unified profiles and use Data Cloud’s insight builder to connect metrics from your Data Warehouse directly to individual profiles.
Field enrichments within Salesforce can then surface insights into your CRM, enhanced by tools like Einstein Next Best Action. For marketing, Data Cloud’s Segmentation and Activation features can leverage these insights to drive targeted campaigns effortlessly.
Some sample use cases include:
- Proactive product recommendations, such as credit repair packages or premium credit cards, based on 3, 6, and 12-month credit score trends.
- Specialized leasing terms based on tenant risk ratings.
- Customer retention and churn predictions based on social media behaviors and survey data.
- Recommended rent based on tenant sales reporting trends and projected cost of occupancy.
- Personalized product offers based on life events, such as student credit cards and college savings plans.
Data Cloud and Snowflake Integration Benefits
This approach offers the best of both worlds:
- Scalable Data Warehouse: Snowflake provides a highly scalable data warehouse solution capable of generating extensive metrics and accessing demographic data through the Snowflake Marketplace.
- Integration with BI Tools: Integrate with powerful BI and visualization tools like Tableau to create visualizations powered by your complete data warehouse.
- Robust Identity Resolution: Use identity resolution to link these insights to specific individuals in your CRM, utilizing zero-copy architecture to minimize credit consumption in Data Cloud.
- Easy Data Integration: Achieve seamless data integration from Snowflake to Data Cloud through configuration rather than code, leveraging Data Cloud’s insight builder without needing SQL queries.
