Hi Trailblazers!
If you're planning to learn Salesforce Data 360 (formerly Data Cloud), here is a simple roadmap to follow.
1. Data 360 Basics
- Introduction, Architecture and Real-Time Use Cases
- Key Features and Benefits
2. Setup and Data Ingestion
- Data 360 Setup and Permissions
- Data Spaces, Data Streams and Connectors
- Zero Copy Integration
3. Data Modelling
- Data Lake Objects (DLOs)
- Data Model Objects (DMOs)
- Data Mapping and Transformations
4. Identity Resolution
- Matching and Reconciliation Rules
- Unified Customer Profiles
5. Insights and Segmentation
- Calculated Insights and Streaming Insights
- Segments and Data Graphs
6. Data Activation
- Activation Targets
- Data Actions and Flow Integration
7. Data 360 with Agentforce
- Structured and Unstructured Data
- Search Indexes and Retrievers
- Data Libraries and Agentforce Integration
8. Security and Practical Experience
- Data Security and Governance
- Monitoring and Troubleshooting
- End-to-End Real-Time Project
Useful Learning Resources
🔗 SFDCINDIA – Salesforce Data 360 Blog
https://sfdcindia.com/blog/salesforce-data-360
🔗 Salesforce Data 360 Learning Trail
https://trailhead.salesforce.com/content/learn/trails/data-cloud-explore-setup-to-activation
🔗 Data 360 Fundamentals
https://trailhead.salesforce.com/content/learn/trails/unlock-your-data-with-data-cloud
🔗 Salesforce Official Documentation
https://help.salesforce.com/s/articleView?id=data.c360_a_data_ingestion.htm&type=5
🔗 Data 360 Consultant Certification
https://trailhead.salesforce.com/credentials/data360consultant
My Suggestion:
Start with Data Streams, DLOs, DMOs, and Data Mapping before moving to advanced topics.
Focus on hands-on practice and try to build at least one end-to-end project.
Which Data 360 topic do you find most challenging?
Let's share our experiences and learn together!
#Data Cloud #Data360 #Agentforce #Trailhead Challenges #TrailblazerCommunity
