Data Cloud (Data 360)

Data Cloud (Data 360)Salesforce's data platform: data streams, DLOs & DMOs, zero-copy, identity resolution, calculated insights, segments, Query API and grounding AI.

Data 360 Architecture and Concepts: Why Salesforce built a data platform, how Data 360 (formerly Data Cloud) is architected as an Iceberg/Parquet lakehouse on Hyperforce, and how data flows from sources through DLOs and DMOs to unified profiles, insights, segments, activation, Agentforce and Tableau.

Ingestion, Data Streams and Modeling: Bring data into Data 360 with native connectors, the Web and Mobile SDKs and the Ingestion API (streaming and bulk), choose the right data stream category and keys, map DLOs to standard and custom DMOs, reshape data with transforms and package it all with data kits.

Identity Resolution and Unified Profiles: How Data 360 turns fragmented source records into unified individuals and accounts: match rules, reconciliation rules, rulesets, the generated unified and link objects, processing, consolidation metrics, consent, and SQL to inspect and debug the results.

Calculated Insights, Segments and Activation: Turn unified data into action: SQL calculated insights with dimensions and measures, streaming insights and data actions, segments with nested and waterfall logic and different publish modes, activation to Marketing Cloud, ads and storage, and enrichment and automation back in CRM with Data 360-triggered flows.

Developing with Data 360: The developer's toolkit for Data 360: Query API generations and the Connect REST SQL endpoint, Profile and Calculated Insights APIs, querying DMOs from Apex and LWC, data graphs, Data 360-triggered automation, vector and hybrid search for RAG, Einstein Studio, DevOps with data kits and sandboxes, testing strategies and security.

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