Unify Data

Use identity resolution to consolidate data from different sources into comprehensive views of your customers and accounts in Data 360.

  • Simplify Real-Time Data Graph Configuration
    Streamline your setup process by removing the Record Caching and User Session Length settings in the Consumption Limits section for real-time data graphs. These settings don’t impact your credit consumption or billing. This update simplifies configuration and helps you focus on settings that directly impact Data 360 usage. When creating a real-time data graph, the Real-Time Consumption Limits section no longer includes the Record Caching or User Session Length fields.
  • 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.
  • 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.
  • Optimize Identity Resolution by Segregating B2B and B2C Data with Filters
    Segregate B2B and B2C records within the same data space to run identity resolution on different audience types by using preprocessing data filters. Process smaller sample datasets to safely test, audit, and refine your matching rules before deploying them to full production workloads. Preprocessing filters act as an upstream layer and use conditional logic applied directly to source data model objects to create broad, partition-like environment boundaries. Filtering out unneeded records optimizes credit consumption by ensuring that identity resolution processes only the records that you need.