Data Stream
A Data Stream in Salesforce Data Cloud is an ingestion pipeline that brings data from an external source into Data Cloud.
Definition
A Data Stream in Salesforce Data Cloud is an ingestion pipeline that brings data from an external source into Data Cloud. Data Streams define the source system, the data schema (mapping source fields to Data Cloud fields), the refresh schedule (real-time, batch, or incremental), and the target Data Model Object. They are the primary mechanism for connecting external data sources like databases, cloud storage, APIs, and Salesforce orgs to Data Cloud.
In plain English
“A Data Stream is a pipeline that brings data into Salesforce Data Cloud from somewhere else. You set up the source, map fields to a Data Model Object, choose how often to refresh, and Data Cloud handles the ingestion. It's how external data shows up in Data Cloud in the first place.”
Worked example
Pebblestone Wines, a DTC wine retailer with three e-commerce platforms and a brick-and-mortar POS, ingests customer signals into Salesforce Data Cloud through five Data Streams: a Shopify Data Stream (real-time webhook), a Marketing Cloud email engagement stream (incremental every 15 minutes), a POS daily batch stream from the in-store system, a Customer Support Case stream from Service Cloud, and a Website-events stream from Segment. Each Data Stream maps source fields to Data Cloud's standard People and Engagement Data Model Objects, runs on its appropriate refresh schedule, and contributes to identity resolution. The five streams together build the unified 360° view of each wine subscriber.
Why Data Stream matters
A Data Stream in Salesforce Data Cloud is an ingestion pipeline that pulls data from an external source into Data Cloud. Configuring a Data Stream involves picking the source system (a database, cloud storage bucket, API endpoint, or another Salesforce org), defining the data schema by mapping source fields to Data Cloud DMO fields, picking a refresh strategy (real-time streaming, scheduled batch, or incremental updates), and specifying the target DMO that will receive the data.
Data Streams are the entry point for external data into Data Cloud. Without them, Data Cloud has nothing to unify. The variety of supported sources (Salesforce orgs, databases, cloud storage, APIs, files, partner connectors) lets organizations pull in customer data from wherever it lives and bring it into the canonical model. The choice of refresh strategy matters: real-time streams support use cases like personalization that need fresh data within seconds, while batch streams are appropriate for less time-sensitive data that updates daily or weekly. Setting up Data Streams thoughtfully is one of the highest-leverage Data Cloud activities.
How organizations use Data Stream
Set up Data Streams from their CRM, e-commerce platform, and email marketing tool, all flowing into the Individual DMO. The streams refresh on schedules appropriate to each source's update frequency.
Built a real-time Data Stream from their production database to Data Cloud for personalization use cases. Customer behavior events flow into Data Cloud within seconds, enabling real-time recommendations.
Uses scheduled Data Streams for nightly bulk loads from their data warehouse. The nightly cadence is appropriate for analytics use cases that don't need real-time freshness.
Trust & references
Hands-on resources to go deeper on Data Stream.
Test your knowledge
Q1. What does a Data Stream do?
Q2. What refresh strategies do Data Streams support?
Q3. Why does refresh strategy matter?
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