What is Salesforce Data Cloud? Posted by
MacLain JohnsonThe short answer: Salesforce Data Cloud is Salesforce’s platform for unifying customer data from every source (Salesforce orgs, data warehouses, external systems) into a single real-time profile of each customer. At Dreamforce 2025 it was renamed Data 360 under the Agentforce 360 brand, and it has become the data foundation that Salesforce’s AI features depend on.
Most companies’ customer data is scattered: a Salesforce org here, a data warehouse there, an e-commerce platform and a support system somewhere else. Salesforce Data Cloud, now officially called Data 360, exists to pull that together. Here is what it does, how it fits into the Salesforce ecosystem, and why it has moved from optional add-on to strategic foundation.
What is Salesforce Data Cloud?
Salesforce Data Cloud is a data platform that connects, harmonizes, and unifies customer data across sources to create a comprehensive, real-time profile of every customer. Rather than physically copying everything into yet another database, it can also connect to external data warehouses such as Snowflake, Databricks, and Google BigQuery with zero-copy access, meaning the data stays where it lives while Salesforce reads it in place.
The product has carried several names over the years, which causes real confusion, so here is the lineage:
Period Name 2020 Customer 360 Audiences 2021 Salesforce CDP (Customer Data Platform) 2022 Salesforce Genie 2023 Salesforce Data Cloud October 2025 onward Data 360, under the Agentforce 360 brand
You will see “Data Cloud” and “Data 360” used interchangeably for a while; they are the same product. Our guide to the Salesforce product name changes covers the full renaming.
What does Salesforce Data Cloud actually do?
- Data unification. Ingests and harmonizes customer data from Salesforce orgs, websites, mobile apps, data warehouses, and third-party systems into one standardized model.
- Identity resolution. Matches records across systems (the same customer as a lead in one org, a contact in another, and a loyalty member in a third) into a single unified profile.
- Real-time processing. Profiles update as new interactions happen, so segments and service views reflect what customers did minutes ago, not last month.
- Segmentation and activation. Builds audience segments on any combination of attributes and behaviors, then pushes them to marketing, advertising, sales, and service channels.
- Grounding for AI. Salesforce’s Einstein and Agentforce features draw on Data Cloud profiles to give AI-generated answers and recommendations accurate, current customer context.
How does Data Cloud fit into the Salesforce ecosystem?
Data Cloud has become the connective tissue of the Salesforce platform. Marketing teams use its segments for personalized campaigns, sales teams see unified customer histories, service agents get complete context on who they are helping, and analytics tools like Tableau read its harmonized data directly. Most importantly for where Salesforce is heading, the Agentforce AI assistants rely on Data Cloud for the customer context that makes their output trustworthy. If your organization plans to adopt Salesforce’s AI features seriously, Data Cloud is the prerequisite investment.
How is Data Cloud different from a traditional CDP?
Traditional customer data platforms are standalone marketing tools: they unify data so marketers can build segments. Data Cloud does that too, but it differs in three ways: it is native to the Salesforce platform, so unified data is usable in sales, service, and commerce workflows rather than marketing alone; it supports zero-copy access to enterprise data warehouses instead of requiring full data duplication; and it feeds Salesforce’s AI layer directly. For organizations already on Salesforce, that native integration is usually the deciding factor.
Getting started with Data Cloud
Data Cloud projects live or die on scoping: which sources to connect first, how to configure identity resolution so profiles merge correctly, and which use case (marketing segmentation, service context, or AI readiness) justifies phase one. CloudMasonry’s Salesforce Data Cloud consulting practice helps organizations plan and implement Data Cloud with a clear first use case rather than a boil-the-ocean data project. Contact us to discuss where Data Cloud fits your roadmap.
Frequently Asked Questions
Is Salesforce Data Cloud the same as Data 360?
Yes. Salesforce renamed Data Cloud to Data 360 at Dreamforce 2025 as part of the Agentforce 360 rebrand. It is the same product; earlier names include Salesforce Genie, Salesforce CDP, and Customer 360 Audiences.
Is Salesforce Data Cloud a CDP?
Salesforce Data Cloud includes everything a customer data platform (CDP) does, such as unifying customer data and building segments, but it goes further: zero-copy connections to data warehouses, native activation across sales, service, and commerce, and grounding for Salesforce’s AI features.
Do I need Data Cloud to use Agentforce?
Agentforce assistants work best when grounded in unified customer data, and Salesforce built Data Cloud (Data 360) as that grounding layer. Simple use cases can run on org data alone, but organizations adopting Agentforce at scale generally implement Data Cloud alongside it.
Does Data Cloud copy all my data into Salesforce?
Not necessarily. Data Cloud supports zero-copy integration with warehouses like Snowflake, Databricks, and Google BigQuery, reading data in place without duplicating it. Data from other sources can be ingested directly when that makes more sense.
MacLain JohnsonThe short answer: Salesforce Data Cloud is Salesforce’s platform for unifying customer data from every source (Salesforce orgs, data warehouses, external systems) into a single real-time profile of each customer. At Dreamforce 2025 it was renamed Data 360 under the Agentforce 360 brand, and it has become the data foundation that Salesforce’s AI features depend on.
Most companies’ customer data is scattered: a Salesforce org here, a data warehouse there, an e-commerce platform and a support system somewhere else. Salesforce Data Cloud, now officially called Data 360, exists to pull that together. Here is what it does, how it fits into the Salesforce ecosystem, and why it has moved from optional add-on to strategic foundation.
What is Salesforce Data Cloud?
Salesforce Data Cloud is a data platform that connects, harmonizes, and unifies customer data across sources to create a comprehensive, real-time profile of every customer. Rather than physically copying everything into yet another database, it can also connect to external data warehouses such as Snowflake, Databricks, and Google BigQuery with zero-copy access, meaning the data stays where it lives while Salesforce reads it in place.
The product has carried several names over the years, which causes real confusion, so here is the lineage:
| Period | Name |
|---|---|
| 2020 | Customer 360 Audiences |
| 2021 | Salesforce CDP (Customer Data Platform) |
| 2022 | Salesforce Genie |
| 2023 | Salesforce Data Cloud |
| October 2025 onward | Data 360, under the Agentforce 360 brand |
You will see “Data Cloud” and “Data 360” used interchangeably for a while; they are the same product. Our guide to the Salesforce product name changes covers the full renaming.
What does Salesforce Data Cloud actually do?
- Data unification. Ingests and harmonizes customer data from Salesforce orgs, websites, mobile apps, data warehouses, and third-party systems into one standardized model.
- Identity resolution. Matches records across systems (the same customer as a lead in one org, a contact in another, and a loyalty member in a third) into a single unified profile.
- Real-time processing. Profiles update as new interactions happen, so segments and service views reflect what customers did minutes ago, not last month.
- Segmentation and activation. Builds audience segments on any combination of attributes and behaviors, then pushes them to marketing, advertising, sales, and service channels.
- Grounding for AI. Salesforce’s Einstein and Agentforce features draw on Data Cloud profiles to give AI-generated answers and recommendations accurate, current customer context.
How does Data Cloud fit into the Salesforce ecosystem?
Data Cloud has become the connective tissue of the Salesforce platform. Marketing teams use its segments for personalized campaigns, sales teams see unified customer histories, service agents get complete context on who they are helping, and analytics tools like Tableau read its harmonized data directly. Most importantly for where Salesforce is heading, the Agentforce AI assistants rely on Data Cloud for the customer context that makes their output trustworthy. If your organization plans to adopt Salesforce’s AI features seriously, Data Cloud is the prerequisite investment.
How is Data Cloud different from a traditional CDP?
Traditional customer data platforms are standalone marketing tools: they unify data so marketers can build segments. Data Cloud does that too, but it differs in three ways: it is native to the Salesforce platform, so unified data is usable in sales, service, and commerce workflows rather than marketing alone; it supports zero-copy access to enterprise data warehouses instead of requiring full data duplication; and it feeds Salesforce’s AI layer directly. For organizations already on Salesforce, that native integration is usually the deciding factor.
Getting started with Data Cloud
Data Cloud projects live or die on scoping: which sources to connect first, how to configure identity resolution so profiles merge correctly, and which use case (marketing segmentation, service context, or AI readiness) justifies phase one. CloudMasonry’s Salesforce Data Cloud consulting practice helps organizations plan and implement Data Cloud with a clear first use case rather than a boil-the-ocean data project. Contact us to discuss where Data Cloud fits your roadmap.
Frequently Asked Questions
Is Salesforce Data Cloud the same as Data 360?
Yes. Salesforce renamed Data Cloud to Data 360 at Dreamforce 2025 as part of the Agentforce 360 rebrand. It is the same product; earlier names include Salesforce Genie, Salesforce CDP, and Customer 360 Audiences.
Is Salesforce Data Cloud a CDP?
Salesforce Data Cloud includes everything a customer data platform (CDP) does, such as unifying customer data and building segments, but it goes further: zero-copy connections to data warehouses, native activation across sales, service, and commerce, and grounding for Salesforce’s AI features.
Do I need Data Cloud to use Agentforce?
Agentforce assistants work best when grounded in unified customer data, and Salesforce built Data Cloud (Data 360) as that grounding layer. Simple use cases can run on org data alone, but organizations adopting Agentforce at scale generally implement Data Cloud alongside it.
Does Data Cloud copy all my data into Salesforce?
Not necessarily. Data Cloud supports zero-copy integration with warehouses like Snowflake, Databricks, and Google BigQuery, reading data in place without duplicating it. Data from other sources can be ingested directly when that makes more sense.
Client Success Stories
Vista Outdoor
The parent company of more than 40 outdoor and sporting brands. Read how CloudMasonry delivered Salesforce Data Cloud and Marketing Cloud across their portfolio.
Packback
A Chicago education technology company. See how CloudMasonry integrated Salesforce Sales Cloud with the data in Packback’s core product.
Millennium Trust
A leading retirement and custody provider. Read how their Salesforce Experience Cloud build connects with AWS and Heroku.
CREXi
A commercial real estate marketplace built on transaction data. See how a high-volume platform company runs Salesforce Sales Cloud.