Topic hub
#Data Cloud
Salesforce Data Cloud is Salesforce's CDP and data lakehouse. Articles below cover data ingestion, identity resolution, calculated insights, segmentation, activation, and the Customer Graph that exposes Data Cloud back to Sales / Service Cloud as live records.
Salesforce Data Cloud vs Microsoft Fabric Customer Insights
Customer data unification in 2026: zero-copy vs lakehouse-native, identity resolution, activation surface, and the right pick by data org maturity.
Vector DB vs CRM-Native Semantic Search: The Real Decision
Bring your own Pinecone or use Data Cloud, Dataverse, Smart CRM semantic search? Cost, latency, governance, and the lock-in math.
Data Cloud Row-Level Formulas: Where They Quietly Kill You
Row-level formulas in Data Cloud look harmless until refresh windows balloon and credit burn doubles. Here are the pitfalls and the fix patterns.
Calculated Insights Explained: From Metrics to Activation
What calculated insights are in Salesforce Data Cloud, how to design them, and how they power segments, activation, and agent grounding.
Data Cloud + Agentforce: 7 Integration Patterns That Work
Seven practical patterns for grounding Agentforce agents in Data Cloud — identity, segments, calculated insights, and when to skip it entirely.
Data Cloud Data Model Fundamentals Every Admin Should Know
The Data Cloud data model explained — DSOs, DMOs, and DLOs — with a practical walkthrough of how data flows from ingestion to activation.
Salesforce Data Cloud Is Now Data 360
Dreamforce 2025 rebrand official for 2026 releases. Part of Agentforce 360 ecosystem — what changes, what doesn't, and how to message it.
Salesforce Data Cloud vs HubSpot: A CDP Comparison
When HubSpot's native data model is enough, when a full CDP matters, and the integration reality.
Data Cloud vs Snowflake vs Databricks: A Straight Comparison
An honest comparison of Salesforce Data Cloud, Snowflake, and Databricks — what each actually does, where they overlap, and how to decide.
Identity Resolution Rulesets: Design Unified Profiles That Hold Up
How to design identity resolution rulesets in Data Cloud — match rules, reconciliation, survivorship, and avoiding common false-merge failures.
Data Cloud Streaming Ingestion: Patterns for Real-Time
How to ingest streaming data into Data Cloud — the API, patterns, idempotency, and operational concerns for real-time use cases.