🧭 Executive Overview: Implementing Batch vs. Streaming in Salesforce Data Cloud
Modern customer engagement requires timely, unified data. Salesforce Data Cloud enables this through two core ingestion approaches: Batch and Streaming. Each serves different business needs and aligns to distinct strategic goals.
Batch Data Ingestion
Purpose: Best for processing large volumes of data on a scheduled basis — ideal for reporting, analytics, and historical data updates.
🔹 How It Works:
- Connects to your existing data sources (e.g., data lakes, databases, cloud storage).
- Data is ingested on a set schedule — daily, hourly, etc.
- Data is mapped into Salesforce’s harmonized data model (via Data Streams and Data Model Objects).
- Supports high-volume use cases like customer master updates, nightly transaction loads, or demographic enrichment.
✅ When to Use:
- Your data doesn’t change frequently or doesn’t require instant action.
- You need scalable, predictable updates to customer profiles.
⚡ Streaming Data Ingestion
Purpose: Designed for real-time use cases — delivering live, event-driven insights to power immediate actions and experiences.
🔹 How It Works:
- Leverages real-time connectors (e.g., Kafka, Kinesis, MuleSoft APIs).
- Data is continuously streamed into Data Cloud as it happens.
- Mapped to Salesforce’s data model and immediately available for activation — such as personalized messaging, real-time segmentation, or fraud detection.
✅ When to Use:
- You require up-to-the-second data for customer engagement or operations.
- You’re enabling intelligent, event-driven experiences — like real-time personalization, behavior tracking, or alerting.
📊 Strategic Considerations
| Criteria | Batch Processing | Streaming Processing |
|---|---|---|
| Latency | Scheduled (minutes to hours) | Real-time (seconds) |
| Use Case Examples | Reporting, master data sync | Personalization, event-triggered journeys |
| Data Sources | Files, databases, cloud storage | Events, APIs, real-time systems |
| Business Value | Operational efficiency, scalability | Customer experience, responsiveness |
🧠 Executive Guidance
- Start with batch if you’re early in your Data Cloud journey. It’s lower complexity and gets foundational data in place.
- Add streaming for differentiated, real-time use cases that drive competitive advantage — especially in marketing, commerce, and service.
- Combine both for a hybrid strategy: Use batch for data depth, and streaming for data freshness.