Peoplewoo - Blogs #DataModelObjectsPeoplewoo - Blogs #DataModelObjectshttps://www.peoplewoo.com/blogs/tag/datamodelobjectsFri, 10 Jul 2026 17:07:32 +0530http://zoho.com/sites/<![CDATA[Integrating Salesforce Marketing Cloud Engagement With Data 360 | Peoplewoo Skills]]>https://www.peoplewoo.com/blogs/post/intrgrating-salesforce-marketing-cloud-engagement-with-data-360-peoplewoo-skillsThis blog explains how Salesforce Data Cloud connects and unifies customer data from different systems—like Salesforce Orgs and Marketing Cloud—into a single, complete view of each person.]]>

Introduction

Imagine having customer data scattered across multiple Salesforce Orgs, Marketing Cloud, and external systems. How do you bring it all together? That is where Salesforce Data Cloud shines.

Data Cloud allows you to stream data from various sources and map them to a single, unified view. Let’s break down how this works—from standard starter bundles to mapping your custom data.


The Power of the "Individual" Object

In Data Cloud, your data flows from Data Lake Objects (DLOs) into Data Model Objects (DMOs). When dealing with profile data—like Leads from one Salesforce Org and Contacts from another—they all represent the same human being.

To achieve true data unification, Data Cloud uses a core profile DMO called the Individual Object.

  • Profile Category Data: Leads, Contacts, and Accounts are mapped here.

  • The Goal: Tie different IDs from different systems to a single Individual ID to build a single source of truth.


Syncing Engagement Data from Marketing Cloud

Beyond profile data, you also need to track how customers interact with your brand. This is EngagementData.

By connecting Salesforce Marketing Cloud in Data Cloud Setup, you can deploy Starter Bundles (Email, Mobile Connect, and Mobile Push). This automatically ingests standard data views like clicks, opens, bounces, and subscribers, mapping them instantly into the Data Cloud ecosystem.


Step-by-Step: Mapping Custom Data Extensions

What if you have custom subscriber data inside a Marketing Cloud Data Extension (DE) that isn't part of a standard bundle? You have to map it manually. Here is how:

  1. Create a New Data Stream: Select Salesforce Marketing Cloud as the source and locate your specific Business Unit and DE folder.

  2. Select the Category & Primary Key: For custom profile data, set the category to Profile and choose your unique identifier (e.g., Subscriber Key) as the Primary Key.

  3. Map to Data Model Entities: * Create a Custom DMO to mirror your Data Extension fields.

    • Link and map your Subscriber Key to the Individual DMO (Individual ID) to ensure unification.

    • Map contact details to standard helper DMOs like Contact Point Email, Contact Point Phone, and Contact Point Address.

Once deployed, Data Cloud runs the stream, seamlessly feeding your custom marketing insights into a unified, actionable customer profile!


Explore Salesforce Data 360 (Data Cloud)

Learn Salesforce Data 360 with real-world ingestion, identity resolution, segmentation, and activation workflows. Build job-ready Data Cloud consulting skills with hands-on practice and interview-focused preparation.

Live Training Udemy Data 360 Course Interview Q&A Course WhatsApp
Learn • Build • Get Certified | Peoplewoo Skills
]]>Thu, 09 Jul 2026 15:01:27 +0530<![CDATA[Mapping Data Streams To DLOs and DMOs In Data 360 | Peoplewoo Skills]]>https://www.peoplewoo.com/blogs/post/mapping-data-streams-to-dlos-and-dmos-in-data-360-peoplewoo-skillsThis guide explains how Salesforce Data Cloud connects raw customer data from different sources and combines it into a single, unified profile.]]>

Raw Data to Customer 360

Unlocking a true 360-degree view of your customer requires pulling data from various platforms into one centralized hub. In Salesforce Data Cloud, this architectural journey follows a seamless path from raw source data to a unified profile.

Here is a quick, easy guide to understanding how your data moves through the cloud.


1. Connecting Data via Data Streams

Every source system contains native assets known as DataSourceObjects(DSOs)—think of standard objects like Leads, Contacts, or Accounts. To bring this data into Data Cloud, you must establish a DataStream.

  • Starter Bundles: Salesforce provides pre-built bundles for Sales and Service Cloud, allowing you to install and connect standard objects instantly.

  • Custom Objects: For unique data sitting outside of standard bundles, you can manually ingest them by selecting the "All Objects" option.


2. Categorizing Your Data

When data streams are configured, the data must be classified into one of three categories. These categories are vital for setting up rules around how data is handled later:

  • Profile: Contains Personal Identifiable Information (PII) like names, phone numbers, and addresses.

  • Engagement: Tracks real-time or batch behavioral data, such as email opens, link clicks, or website visits.

  • Other: Reserved for auxiliary data that does not fit into profile or engagement definitions.


3. From Data Lake Objects (DLO) to Data Model Objects (DMO)

Creating a data stream automatically generates a Data Lake Object (DLO). Think of a DLO as the physical container that holds your raw data.

To make this raw data usable, you must map the DLO to a Data Model Object (DMO) within the standard Customer 360 model. While starter bundles map fields like Contact Point Phone or Contact Point Email automatically, custom data requires manual mapping to organize it correctly.


4. Unifying Profiles with the Individual Object

A single customer might exist as a Lead in one Salesforce org, a Contact in another, and a subscriber in Marketing Cloud. To prevent duplicate profiles, Data Cloud maps all profile data to a core standard DMO called the IndividualObject.

By linking various system IDs to a single Individual ID, Data Cloud resolves identities across multiple connected orgs, creating a singular, unified source of truth for your entire enterprise.


Explore Salesforce Data 360 (Data Cloud)

Learn Salesforce Data 360 with real-world ingestion, identity resolution, segmentation, and activation workflows. Build job-ready Data Cloud consulting skills with hands-on practice and interview-focused preparation.

Live Training Udemy Data 360 Course Interview Q&A Course WhatsApp
Learn • Build • Get Certified | Peoplewoo Skills
]]>Fri, 26 Jun 2026 10:22:36 +0530<![CDATA[Data Streams, DLO & DMO in Data 360 | Peoplewoo Skills]]>https://www.peoplewoo.com/blogs/post/data-streams-dlo-dmo-in-data-360

How Salesforce Data Cloud Works

A simple breakdown of how data moves from isolated systems into a single, unified view.

Connecting the Source: DSOs and Data Streams

Before Data Cloud can harmonize your data, it requires a secure ingestion pipeline to your external environments.

  • Data Source Objects (DSOs): These are the native objects residing inside your source systems—such as the Lead, Contact, or Account objects within Salesforce Sales Cloud.
  • Data Streams: The actual functional connections established to transition data from your DSOs into Data Cloud. Data Streams seamlessly support both real-time integrations and batch uploads.

To accelerate implementation, Salesforce offers pre-built Starter Bundles (e.g., Sales Cloud and Service Cloud bundles). Deploying these bundles automates the connection setup for standard enterprise objects, removing the need for manual configuration.


Data Categorization: Profile vs. Engagement

When connecting custom objects or external data lakes, Data Cloud requires you to categorize the incoming data schema. This taxonomy determines how data behaves during identity resolution workflows.

CategoryDefinitionEnterprise Examples
ProfilePersonally Identifiable Information (PII) defining who the customer is.Leads, Contacts, Accounts (Names, Emails, Addresses)
EngagementBehavioral tracking data detailing actions taken by the customer.Email opens, link clicks, website visits, form downloads
OtherSupplementary data that does not strictly match Profile or Engagement schemas.Product catalogs, support cases, operational logs

The Architecture: DLOs vs. DMOs

The journey from raw data ingestion to standard data modeling relies on two foundational architecture components:

 1. Source System / DSO (Raw Source)
 ↓ Connected via Data Stream
 2. Data Lake Object / DLO (Physical Storage Container)
 ↓ Standardized via Data Mapping
 3. Data Model Object / DMO (Unified Customer 360 Shape)


Creating a Data Stream automatically provisions a corresponding Data Lake Object (DLO). The DLO serves as the exact physical storage container for your raw data inside Data Cloud. However, at this stage, the data is unstructured and unaligned with the broader ecosystem.

To make this information usable, fields from the DLO must be mapped directly to a Data Model Object (DMO). DMOs are the standard semantic templates that comprise the global Customer 360 model.


4. The Foundation of Unification: The Individual Object

The single most critical DMO for true profile unification is the Individual object.

In complex multi-org enterprise environments, a single human being often exists under completely different unique keys across multiple systems. They might be tracked as a Lead ID in Sales Cloud, a converted Contact ID in a secondary business unit, and a Subscriber Key within Marketing Cloud.

By mapping every single profile-category data stream to the central Individual Object, you establish a universal anchor point. This mapping enables Data Cloud's Identity Resolution engines to successfully cross-reference disparate source records and consolidate them into one single, cohesive, and actionable customer profile.

Explore Salesforce Data 360 (Data Cloud)

Learn Salesforce Data 360 with real-world ingestion, identity resolution, segmentation, and activation workflows. Build job-ready Data Cloud consulting skills with hands-on practice and interview-focused preparation.

Live Training Udemy Data 360 Course Interview Q&A Course WhatsApp
Learn • Build • Get Certified | Peoplewoo Skills

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