Understanding Salesforce Data 360 Objects: The Core of the Unified Customer Profile

Source: Dev.to

Introduction

Salesforce Data 360 (formerly Data Cloud) is becoming the foundational layer for most new Salesforce innovations. It blends real‑time data orchestration with an enterprise‑grade architecture, enabling the unification of customer data and activation of insights. Unlike traditional Salesforce Clouds that rely on a common core platform and relational databases, Data 360 uses a distinct technology stack built for petabyte‑scale data, leveraging services such as DynamoDB for hot storage and Amazon S3 for cold storage.

The platform’s architecture is organized through a set of layered objects that govern how data is ingested, harmonized, and ultimately activated.

Data Object Hierarchy in Salesforce Data Cloud

Data flows through a defined sequence of objects as it moves from its external source into the unified Customer 360 profile.

Data Source (The Origin)

The external system or service that provides the raw data (e.g., Sales Cloud, Commerce Cloud).

Data Stream (The Entity Path)

A Data Stream is an entity extracted from a specific Data Source—such as “Contacts” from Sales Cloud or “Orders” from Commerce Cloud. When setting up a Data Stream, it must be assigned a category: Profile, Engagement, or Other. A single Data Source can contain multiple Data Streams.

Data Source Object (DSO: The Raw Staging Area)

The Data Source Object (DSO) is where a Data Stream is first ingested. It acts as a temporary staging store that holds the data in its raw, native file format (e.g., CSV). Minor transformations can be applied using formulas on fields at ingestion time.

Data Lake Object (DLO: The Prepared Data Store)

The Data Lake Object (DLO) is the next stage and the first object available for inspection and preparation. It is the product of a DSO plus any transformations applied. DLOs are stored in Amazon S3 as Apache Parquet files—column‑oriented for efficient storage and retrieval. They are typed, schema‑based, and materialized views.

Data Spaces—logical partitions used for security and organization—allow administrators to filter DLOs and assign them to specific user groups, ensuring each group accesses only relevant data.

Data Model Object (DMO: The Canonical View)

The Data Model Object (DMO) provides a virtual, non‑materialized view into the data lake and is critical for harmonization and activation.

• Canonical Model: DMOs align with the Customer 360 Data Model, offering a standard set of pre‑defined attributes (standard objects). Custom DMOs can also be created.
• Virtual Nature: Queries against a DMO are not stored; they always reflect the current snapshot of the underlying DLOs.
• Inheritance and Relationships: A DMO inherits its category from the first DLO mapped to it. It can have standard or custom relationships (one‑to‑one or many‑to‑one) with other DMOs, similar to standard Salesforce objects. Currently, there are 89 standard DMOs supporting various entity use cases.

Implementation Best Practices

• Focus on Traits, Not Raw Events
  Avoid “shoving exhaustive data into CRM objects.” Keep high‑cardinality events (e.g., clickstream data) in Data 360 (the DLO layer) and publish only summarized traits back to Salesforce CRM objects (such as Opportunity or Case) for reporting and coaching.

• Unification vs. Golden Record
  Data 360’s unification merges data from multiple sources into a unified view for activation without altering the original data. It is not a traditional “golden record” that overwrites source systems.

• Start Small and Model Wisely
  Success depends on modeling data for activation, not just reporting. Adopt a crawl‑walk‑run approach: begin with a single use case to learn ingestion, unification, and activation before scaling up.

Understanding Data Cloud’s layered object model—Source → Stream → DSO → DLO → DMO—is akin to a manufacturing process: each stage refines raw material until it becomes the final, usable form that powers personalization and business action across the entire Salesforce ecosystem.