Salesforce Data Cloud is now called Data 360. It is the data engine built into the Salesforce platform: it connects data from Salesforce and outside systems, maps it to one data model, links records that belong to the same customer into unified profiles, and makes that data usable in segments, automation, analytics and Agentforce agents, often without copying it.
This guide explains what changed with the rename, how Data 360 works, the objects your team will work with, how it compares with a data warehouse, what it costs at list price, and how to plan a first use case. If you are scoping a project, see our Data 360 implementation services.
Is Salesforce Data Cloud the same as Data 360?
Yes. The Salesforce Data 360 page says "Salesforce Data 360 is the official new name for what was previously called Data Cloud." Salesforce also says existing Data Cloud agreements and pricing are honored through the end of the current term, with renewals handled by your account executive.
The Data 360 name is part of the Agentforce 360 launch. Salesforce's 13 October 2025 press release announced general availability of Agentforce 360 and described it as four parts: the Agentforce 360 Platform, Data 360, Customer 360 Apps and Slack. Data 360 is described there as "the trusted, unified data layer that gives every agent context."
For buyers, the rename matters mostly in search and in documentation. Many Trailhead modules, help articles and job descriptions still say Data Cloud. They describe the same product. In this article, Data 360 and Data Cloud mean the same thing.
How does Salesforce Data 360 work?
Salesforce's guide calls Data 360 "the only data engine native to Salesforce." Trailhead's stages of Data 360 unit groups the work into three stages, summarized below with the main features used in each.
| Stage | What happens | Main features |
|---|---|---|
| Connect Data | Bring in structured and unstructured data from Salesforce orgs, databases, cloud storage and SaaS tools, or query it where it lives | Data streams, 200+ prebuilt connectors, zero copy federation |
| Harmonize and Unify | Clean and transform data, map it to a common model, apply governance, and link records for the same person or account | Transforms, data model objects, data spaces, identity resolution rulesets, unified profiles |
| Analyze and Act | Calculate metrics, build audiences and trigger actions in Salesforce apps, Agentforce, analytics, ad platforms and other systems | Calculated and streaming insights, segments, activations, data actions, Flow |
Under the hood, the Salesforce Architects Data 360 guide describes a lakehouse "based on Iceberg/Parquet," plus a real-time layer that processes web and mobile events in milliseconds. That is why Data 360 can handle both large historical datasets and in-session personalization.
What are the core building blocks of Data 360?
Most confusion in Data 360 projects comes from the vocabulary. These are the terms your admins, architects and marketers will use every week.
| Term | What it is | Why it matters |
|---|---|---|
| Data stream | A connection that brings data from a source into Data 360 | Defines what data arrives, how often and into which data space |
| Data lake object (DLO) | The storage layer that holds ingested or federated data | Raw and transformed source data lives here before mapping |
| Data model object (DMO) | "The final, harmonized and structured data layer," with objects such as an individual or an order | Segments, insights and activations work on mapped DMOs, not raw DLOs |
| Data space | A logical container that separates data and metadata by business unit, region or brand | Controls who sees which data, which matters for multi-brand companies |
| Identity resolution ruleset | Match rules and reconciliation rules that decide which records belong to the same person or account | The quality of every profile, segment and agent answer depends on it |
| Unified profile | Links data from many sources into a single profile | Gives sales, service, marketing and agents the same view of a customer |
| Calculated insight | A metric "based on stored data," such as a customer's average order spend | Turns raw records into numbers you can segment and act on |
| Streaming insight | A query "based on real-time data," such as a shopper entering a store's geofence | Drives near real-time actions through data actions |
| Segment | An audience built from unified profiles | The unit you publish to marketing, advertising and service channels |
| Activation | Delivery of segment members and attributes to a target system | Where the data starts to change customer experience |
| Data graph | A denormalized view that combines a profile with related records and insights | Supplies customer context for personalization and generative AI prompts |
One point surprises many teams. The architecture guide says a unified profile is not "a golden record." Identity resolution links source records rather than overwriting them, so your source systems stay the system of record. Our guide to Data 360 identity resolution covers match and reconciliation rules in more depth.
How fast is Data 360 data?
"Real time" means different things for different features. Planning around the actual cadence avoids broken expectations at launch. The figures below come from the Salesforce Architects guide.
| Feature | Typical cadence |
|---|---|
| Real-time layer (web and mobile events) | Milliseconds |
| Real-time segments | Milliseconds, but they cannot use exclusion criteria or nested segments |
| Identity resolution on small batches of changes | As often as every 15 minutes |
| Standard segments, Rapid Publish | 1 to 4 hours |
| Standard segments | A minimum of 12 hours up to 24 hours |
If a use case needs a decision during a live web session, design it on streaming data and the real-time layer. If it is a weekly campaign, standard segments are cheaper and simpler.
What is zero copy, and does Data 360 replace a data warehouse?
Zero copy lets Data 360 use data that stays in another platform. The Salesforce Data 360 page says you can "connect directly to platforms like Snowflake and Databricks with no duplication and no delays," and the architecture guide lists federation with Snowflake, Redshift, BigQuery and Databricks among other sources. Salesforce's pricing page lists zero-copy integrations as free to set up, with cost coming from how the data is used.
The architecture guide is also clear that "Data 360 does not replace existing enterprise investments." In practice, each platform has a different job.
| Question | Data 360 | Data warehouse or lakehouse | Salesforce CRM objects |
|---|---|---|---|
| Main job | Unify and activate customer data inside Salesforce | Store and analyze enterprise data at scale | Run sales, service and other business processes |
| Typical users | Marketers, service and sales teams, agents, admins | Data engineers and analysts | Sales, service and operations users |
| Identity resolution | Built in, with rulesets and unified profiles | Built by your data team | Duplicate rules on individual objects |
| Acting on data | Segments, activations, data actions, Flow and Agentforce | Needs reverse ETL or integration to act | Native workflows on the record |
| Relationship | Reads from the warehouse through zero copy and can share insights back | Stays the analytics system of record | One of many Data 360 sources |
A useful rule: keep heavy analytics and long-term history in the warehouse, and use Data 360 for the customer context that people and agents act on inside Salesforce.
Is Data 360 a customer data platform?
It includes CDP capabilities, but Salesforce positions it more broadly. The Salesforce Data 360 guide says it is "more than a Customer Data Platform (CDP)" because it collects, unifies and activates data, and that its uses reach beyond marketing to sales, service and commerce.
The difference shows up in where the data goes. A marketing-only CDP feeds campaigns and ad audiences. Data 360 also puts insights on Salesforce records, triggers Flow automation and supplies context to Agentforce agents, all governed by the same data spaces and policies.
How does Data 360 power Agentforce?
Salesforce calls Data 360 "the essential data foundation for Agentforce." Its Agent Context Engine, according to the Data 360 page, "continuously enriches structured database records and unstructured documents." The October 2025 launch added Intelligent Context, which lets agents use unstructured content such as "PDFs or diagrams," and Tableau Semantics, which standardizes business metrics through the Customer 360 Semantic Data Model.
For a working agent, that context arrives in two ways:
- Structured context from unified profiles, data graphs and calculated insights, so the agent knows who the customer is and what they bought.
- Unstructured context through retrieval: content such as knowledge articles, case text and files is chunked into a search index, and a retriever passes the relevant parts into the agent's prompt.
Our guide to Data 360 for Agentforce grounding walks through search indexes, retrievers and the Agentforce Data Library. For agent delivery, see Agentforce implementation.
How much does Salesforce Data 360 cost?
Salesforce describes Data 360 pricing as consumption-based. Its pricing page showed three models when we read it on 11 November 2026.
| Model | List price | What is included |
|---|---|---|
| Flex Credits | $500 per 100,000 Flex Credits | Credits used for any Data 360 action; pre-purchase, pay-as-you-go and pre-commit options; credits can move between Data 360 and Agentforce |
| Profiles | $240 per 1,000 profiles per year | Profile-building actions included, plus 1 Flex Credit per profile |
| Enterprise Profiles | $420 per 1,000 profiles per year | Everything in Profiles, 2 Flex Credits per profile, and Data Masking and Ad Audience add-ons |
Salesforce also lists free batch data ingestion and zero-copy integrations, stating that "Bringing data into Data 360 is free." Its guide says Salesforce customers can provision Data 360 for free "with a limited amount of storage and consumption credits." Salesforce notes the pricing page is for information only and subject to change, so confirm your quote with your account executive.
What drives the bill is usage: streaming ingestion, identity resolution runs, calculated insights, segment publishing, activations and agent actions. The cheapest projects are the ones that size refresh cadence and profile counts to the use case before anything is switched on.
What do enterprises use Data 360 for?
The use cases below follow the features Salesforce documents. Each one starts with a unified profile and ends with an action someone or something takes.
- Service. Show agents and AI agents a customer's orders, open cases and recent web activity on one record, and trigger a case when a streaming insight crosses a threshold.
- Sales. Put product usage, engagement scores and account health on Account and Opportunity records, and route leads on calculated insights.
- Marketing. Build segments from unified profiles and activate them to Marketing Cloud or ad platforms, with consent applied before delivery.
- Agentforce. Ground agents in unified profiles and indexed content so answers reflect the customer in front of them.
- Analytics. Share Data 360 insights back to the warehouse, or report on them in Salesforce, so teams work from the same numbers.
How do you implement Salesforce Data 360?
Data 360 projects go wrong when they start with "connect everything." They go right when they start with one outcome. This is the order our architects follow.
- Pick one use case with an owner. For example, a unified service view, a renewal segment or customer context for one agent. The use case decides which sources, fields and refresh cadence you need.
- List sources and choose ingest or zero copy. Keep large warehouse tables in place through zero copy where it fits; ingest what needs transformation or real-time handling.
- Design data spaces and access. Decide early whether brands, regions or business units need separate data spaces, because it shapes everything that follows.
- Map to the data model. Map DLO fields to standard DMOs first and add custom objects only where the standard model has no fit.
- Build and test identity resolution. Test match rules on known customers and look for false merges before any segment or agent relies on the profiles.
- Define insights and segments in writing. Agree what each metric means, so marketing, sales and finance count the same way.
- Activate once, then measure credits. Publish to one target, watch consumption for a few cycles, and adjust cadence before adding the next use case.
Our fixed-scope Data 360 Quickstart follows this path for one use case, from data streams to a live activation, with scope and price fixed in writing after a scoping call.
Frequently asked questions
Is Salesforce Data Cloud the same as Data 360?
Yes. Salesforce says Data 360 is the official new name for what was previously called Data Cloud. The name appears as one of the four parts of Agentforce 360, which Salesforce announced at Dreamforce in October 2025, and Salesforce says existing Data Cloud agreements are honored through the end of the current term.
Is Data 360 a customer data platform (CDP)?
It includes CDP capabilities such as identity resolution, unified profiles, segmentation and activation, but Salesforce positions it as more than a CDP. Its data also feeds sales, service, commerce, analytics, Flow automation and Agentforce agents, not only marketing.
Does Data 360 replace Snowflake or Databricks?
No. Salesforce's architecture guide says Data 360 does not replace existing enterprise investments. It can federate with warehouses and lakehouses such as Snowflake, Databricks, BigQuery and Redshift through zero copy, so data can be used in Salesforce without being duplicated.
How much does Salesforce Data 360 cost?
Pricing is consumption-based. On 11 November 2026, Salesforce listed Flex Credits at $500 per 100,000 credits, Profiles at $240 per 1,000 profiles a year and Enterprise Profiles at $420 per 1,000 profiles a year. Batch ingestion and zero-copy integrations are listed as free.
Can I try Data 360 for free?
Salesforce says its customers can provision Data 360 for free with a limited amount of storage and consumption credits. That is enough to test a small use case, but plan credit use before you connect large or streaming sources.
Do I need Data 360 to use Agentforce?
Not for every agent, but Salesforce calls Data 360 the essential data foundation for Agentforce. Retrieval over documents, search indexes and retrievers, the Agentforce Data Library and unified customer profiles all run on Data 360, so most agents that need context beyond a single record use it.
Plan your first Data 360 use case with an architect
Techila Global Services is a Salesforce Summit Partner, founded in 2012 and headquartered in Frisco, Texas, with 350+ Salesforce professionals holding 500+ Salesforce certifications across 700+ projects, including 15+ Agentforce programs. Our architect-led Data 360 team can help you choose the first use case, size credits and design identity resolution before you commit.
Talk to our Data 360 team about your sources and the outcome you want first.