Salesforce Data 360 Solutions

Data 360, formerly Data Cloud, is Salesforce's layer for bringing customer data together, unifying it into profiles and making it usable in CRM, marketing, analytics and AI agents. Salesforce's own FAQ says Data 360 "is the official new name for what was previously called Data Cloud", so older documentation, Trailhead modules and partner content that say Data Cloud describe the same product.

This page is our Data 360 solution centre: the problem, the reference architecture, and every capability we cover, linked to the page that explains it in depth.

The business problem

Customer data sits in CRM, marketing, commerce, a warehouse and web analytics, each with its own identifiers. The result is duplicate messages, segments nobody trusts, inconsistent consent and AI agents answering from partial context. Data 360 ingests data into a common model, resolves identities and exposes unified profiles, insights and segments to the systems that act on them. It does not fix poor source data, and it adds jobs, costs and permissions to run, so plan for both.

Reference architecture

Our Data 360 reference architecture shows the layers, trust boundaries and failure points in one diagram, and the Data 360 architecture guide explains each layer in depth. This is a reference design: for each implementation we validate the APIs, editions, permissions and connectors that apply to your org.

Capability map

Each capability below links to the page where we cover it in depth. Where no dedicated page exists yet, the capability is part of our Data 360 consulting scope.

• Readiness: start with the Data 360 readiness checklist or the data and personalisation readiness assessment.
• Source discovery and streams: choosing data stream ingestion patterns.
• DLO and DMO mapping: Data 360 ingestion and modelling, DLO vs DMO and mapping custom sources.
• Transforms: batch vs streaming transforms.
• Identity resolution and unified profiles: our identity resolution service, how match rules work and designing unified profiles.
• Segmentation and calculated insights: our segmentation and insights service and real-time segmentation.
• Activation: Data 360 activation to Marketing Cloud, CRM, ads and storage, and to Braze only through an integration layer, since Braze is not a documented native target.
• CRM and marketing integration: Data 360 and Marketing Cloud and Data 360 and Braze.
• Consent, governance and data quality: Data 360 governance and data quality checks before identity resolution.
• Monitoring and performance: monitoring jobs and refresh schedules and segmentation and activation troubleshooting.
• Migration and release management: DevOps and release management and the phased Data 360 implementation guide.
• Operational support: managed Salesforce support.

Latency and processing: what Salesforce states

Data 360 is often described as real time, but timing depends on the path. Salesforce documents these figures:

Identity resolution runs, batch transforms and segment publishes add their own timing. We design each use case around the path it needs and do not promise real time where sources cannot support it.

Data flows and integration patterns

Salesforce sources use what Salesforce calls "zero cost connectors"; others arrive by file, Ingestion API, SDK or zero copy federation with Snowflake, Databricks, Redshift or BigQuery. Outbound, segments go to activation targets and calculated insights trigger data actions to Platform Events, Marketing Cloud or a webhook. Destinations without a native target need an integration layer.

Security boundaries

Every activation target and webhook is a point where data leaves your Salesforce trust boundary. Targets store destination credentials, so treat them as privileged configuration and keep segment builders separate from target managers.

Failure handling

Common failures are ingestion errors, mapping changes that break DMOs, over- or under-merging identity runs and partial activations. We add checks at each layer and reconcile counts from source to destination.

Deployment model

Data 360 is provisioned by Salesforce for your org. GeekMidst works remotely from India, in your environments under your access policies, and hands over runbooks for each job.

Testing strategy

Use representative data. Check mappings against source records, test identity rules with known duplicates, compare segment counts with an independent query, and verify records at the destination.

Operational monitoring

Track ingestion, identity jobs, segment publishes and activations. Alert on failures and on unusual count swings, which usually signal an upstream change.

Licensing, capacity and prerequisites

• Data 360 must be provisioned for your org, and some products depend on it: Salesforce Personalization and Marketing Cloud Personalization+ both require Data 360.
• Processing has a cost. Salesforce notes that turning off "Run jobs automatically" for identity resolution can reduce it, and its Agentforce ROI calculator says it excludes Data 360 credit costs, so model consumption with your account team.
• The hosted Data 360 MCP server's calls count toward Connect API limits and Flex Credits.
• We do not quote prices. Check your contract and Salesforce's current pricing.

Sources

• https://www.salesforce.com/data/
• https://developer.salesforce.com/docs/data/data-cloud-dev/guide/dc-object-model.html
• https://developer.salesforce.com/docs/data/data-cloud-ref/guide/c360a-real-time-ingestion-api.htm
• https://developer.salesforce.com/docs/data/data-cloud-int/guide/c360-a-mobile-web-datastream.html
• https://www.salesforce.com/data/connectivity/zero-copy/
• https://www.salesforce.com/news/stories/expanding-headless-360-enterprise-capabilities/