Salesforce Data Cloud

What is a Data Cloud?  

Salesforce Data Cloud unifies all your company's data on the Einstein 1 Platform, giving every team a 360-degree view of each customer. It combines data from various sources, both internal and external, into a single, easy-to-access model. This helps your sales, service, and marketing teams deliver personalised experiences and drive automation and AI.

Data Cloud gathers data from apps, systems, emails, images, and more to create a complete customer profile. This unified view helps your team understand current needs and anticipate future ones, boosting productivity and customer value.

With Data Cloud, you can consistently provide personalised experiences, leading to higher customer satisfaction, loyalty, and business growth. It ensures everyone has the right information at the right time to meet customer needs in real-time.

Benefits of Data Cloud

How does the salesforce data cloud work?

Salesforce Data Cloud, part of the Einstein 1 Platform, helps teams get a complete view of a customer's profile and understand their behavior, interests, and preferences. 

Here’s how it works:

Connecting Data Sources

• Unify Data: Gather data from various places like spreadsheets, databases, AWS, and Google Big Query. Data Cloud connects and unifies all this data on Salesforce and from external sources to create a comprehensive and trusted customer view.
• Integrations: Use pre-built connectors and seamless integrations to pull data from different internal and external systems.

Harmonizing Data

• Combine Data: Make sure all the gathered data works well together. Data Cloud, built on Salesforce’s metadata model, allows easy access and use of this data across Salesforce apps like Commerce Cloud, Sales Cloud, Marketing Cloud, and Service Cloud.
• Simplify Data Mapping: Use point-and-click mapping and pre-configured bundles to automatically harmonise and standardise disparate data into a single model.

Activating Data

• Utilise Data: Once unified and harmonised, the data can be used across all Salesforce apps and external systems. This enables automation of tasks, triggering workflows, and creating new processes to improve operational efficiency.

Is the salesforce Data Cloud CDP?

Salesforce Data Cloud, previously known as Salesforce CDP, is not just a rebrand but an evolution. While it shares the same purpose and benefits as CDP, it extends its capabilities across the entire Salesforce Customer 360 platform, covering marketing, sales, service, and more. Data Cloud enhances the original features of CDP, such as data ingestion, unification, identity resolution, and activation, making significant improvements and expanding its functionality.  

Salesforce Data Cloud Architecture

Data Model Object (DMO)

Unlike DSOs and DLOs that use a physical data store, a Data Model Object (DMO) provides a virtual view into the data lake. The results from a DMO query are not stored but are always based on the current data snapshot in the DLOs. DMOs can include attributes from different Data Streams, Calculated Insights, and other sources.  

Key Features of DMOs

Category Inheritance

• DMOs inherit categories from the first DLO mapped to the
• After inheriting a category, only DLOs with the same category can be mapped to the DMO.

Standard and Custom Objects

• DMOs offer a canonical data model with predefined attributes, similar to Salesforce objects.
• Custom DMOs, referred to as custom objects, can also be created.
• DMOs can have standard or custom relationships with other DMOs, structured as one-to-one or many-to-one relationships.

Data Object Subject Areas

• DMOs are organized into different subject areas to support various use cases. There are currently 89 standard DMOs, and the number continues to grow.

Example Subject Areas

• Case: For service and support cases.
• Engagement: Tracks interactions like email engagements (send, open, click).
• Loyalty: Manages reward and recognition programs.
• Party: Represents attributes related to individuals, like contact or account information.
• Privacy: Tracks data privacy and consent preferences.
• Product: Defines attributes related to products and services.
• Sales Order: Defines past and forecast sales by product.

Example DMOs in Sales Order Data Object

• Sales Order: Information about current and pending sales orders.
• Sales Order Product: Attributes related to specific products or services.
• Sales Store: Represents a retailer.
• Order Delivery Method: Defines different order and delivery methods for fulfillment.
• Opportunity: Represents an ongoing sale.
• Opportunity Product: Connects an Opportunity to the Product(s) it represents.