Transform your raw data, map to the Customer 360 Data Model, and build data graphs in Data 360.
- Enhance Real-Time Data Graph Queries with Out-of-the-Box Contact Lookup
Query unified data graphs using common contact keys like email and phone numbers, independently of your specific identity resolution rules. Previously, querying Data Graphs required specific identifiers defined in identity resolution rules. With Out-of-the-Box (OOTB) Contact Lookup, you can retrieve real-time data graphs using a single email address or a single phone number per request. - Scale Your Architecture with Increased Data Graph Limits
Build more comprehensive data architectures by creating up to 25 data graphs in a single deployment. Previously, the limit of 10 data graphs restricted your ability to scale across multiple departments or specialized workflows. With this increased capacity, you can deploy multi-domain architectures and specialized data graphs for different AI agents to ensure each use case has the data structure it requires. - Adopt Streaming for Faster Data Graph Updates
Keep your data current with streaming data graphs that update as soon as the underlying data changes. Previously, you had to manually determine the refresh frequency for your data graphs, which sometimes led to stale data. Now, underlying data model object (DMO) data changes automatically trigger updates and provide faster, near real-time refreshes. This predictable refresh behavior makes your SLAs more reliable and gives Agentforce agents or personalization engines access to the most up-to-date Customer 360 profiles. - Create Batch Data Transforms by Using Custom Code with Code Extension
With code extension in Data 360, you can create batch data transforms using your custom Python code. If native batch data transforms don't meet your business requirements, use code extension to author, debug, and deploy your transform logic and then create batch data transforms that use the deployed logic. - Data Transform Schedules Now Packaged with Data Kits
When you add a scheduled batch data transform to a Data Kit and install it on another org, the transform's schedule is now included in the deployment. Previously, schedules weren't included in Data Kit deployments, so you had to re-create them manually in each destination org. - Preview Your Data Inline with Data Lens in the Data Transforms Builder (Beta)
Use Data Lens directly in the Data Transforms Builder to get a live preview of your data at each node, so you can profile data quality and make informed transform decisions without leaving the builder. - Speed Up Data 360 Setup with Simple Start
Remove manual configuration and sync your standard Salesforce CRM objects directly to Data 360. Instead of spending weeks installing standard app bundles, automatically sync your Salesforce CRM object metadata, including data streams, data lake objects (DLOs), and data model object (DMO) mappings. You consume usage-based credits only when you manually activate data streams and ingest data. - Track Past Refresh Events in Data Graph Refresh History
View a detailed historical log of past data graph refresh and activation events directly within the user interface. This new feature provides comprehensive visibility into your data processing pipelines, allowing you to see exactly when a data graph was last refreshed, the duration of the processing cycle, total record counts, and the success or failure status of past runs. - Configure Sort and Limit Filters for Calculated Insight Nodes in Data Graphs
Limit the number of records included at a calculated insight (CI) node in your data graph's JSON output with sort and limit filters. Specify a sort field and sort order to control which records are prioritized. You can now apply the sort and limit filter previously available only for data model object (DMO) nodes to CI nodes. - Query Data Graphs Fields and Subgraphs with Projections
Use Data Graph projections to retrieve the specific fields and data model objects (DMOs) you need from your Data Graphs. Projections reduce data transfer sizes and enable you to tailor Data Graph responses for specific use cases like LLM grounding, agent workflows, and downstream applications. - Deploy Data Graphs Across Data Spaces with Deterministic Naming
Deploy data graphs with the same base name to multiple data spaces in the same org. When you deploy a data graph through a data kit workflow ( UI and POST API) specifically, Data 360 prefixes the API name with the target data space name, so your data graphs coexist across data spaces without naming collisions.