Explore the Underlying Data Architecture

Learning Objectives

After completing this unit, you’ll be able to:

• Identify the data layers in Data 360.
  
• Describe the role each data layer plays in Marketing Cloud Next.
  
• Distinguish between components that draw from DLO versus the data graph.
  

Before You Start

Before you start this badge, consider completing this recommended content.

• Data 360 Setup
  
• Data Graphs in Data 360
  
• Data 360 in Flows
  

Data in Marketing Cloud Next

In Marketing Cloud Next, data powers everything from audience selection to personalization and decisioning. At first glance, it might seem like any data available in Data 360 should be ready to use across the system.

But that’s not always the case.

Behind the scenes, data moves through multiple layers before it becomes available for different use cases. Each layer plays a specific role in how data is stored, connected, and ultimately used.

In this module, you'll learn how these layers work together through the story of Linda Rosenberg, the new Marketing Cloud Next administrator at Cloud Kicks.

Cloud Kicks, a sneaker brand, runs seasonal campaigns, manages a customer loyalty program, and delivers personalized marketing experiences across channels. Linda’s first assignment is to work with the marketing team to launch a campaign targeting customers who recently bought running shoes. The campaign includes a personalized email that displays each customer’s loyalty tier—Silver, Gold, or Diamond—and routes them accordingly:

• Gold and Diamond members receive a discount offer.
  
• Silver members receive a free shipping offer.
  

Campaigns in Marketing Cloud Next are typically created and managed by marketing managers. For the purposes of this module, Linda (as the admin) takes on this role and walks through both the configuration and the campaign setup.

Linda opens Marketing Cloud Next, ready to build a campaign, but immediately hits two walls:

• There's no segment for running shoe buyers yet.
  
• The loyalty tier field isn’t available for the decision split.
  

Before Linda can troubleshoot, she needs to understand where Marketing Cloud Next gets its data and why some of it isn't available everywhere. The answer lies in three distinct data layers.

Role of The DMO Layer

Maya is a Cloud Kicks customer. She's in the e-commerce system as a shopper, in Agentforce Service as a contact, and in the loyalty app as a member. Three systems, three records, all describing the same person. Without a way to connect them, Maya looks like three different customers. That's where the data model object (DMO) layer comes in.

Here's how Data 360 brings Maya together into a single, unified profile:

• First, raw data from each source lands in a data lake object (DLO) exactly as it came in, unprocessed and in whatever format the source system uses. Think of a DLO as the intake area. Data arrives here first.
  
• From there, Data 360 maps the data to standardized DMOs. This is what makes a member record from the loyalty app and a contact from Agentforce Service recognizable as the same type. DMOs give every source a common structure to work from.
  
• Finally, identity resolution stitches those standardized records together into a single Unified Individual profile. While Maya’s three DMO records still remain, identity resolution creates a new, resolved version of Maya that brings them all together in one unified view.
  

This unified profile is what powers segmentation in Marketing Cloud Next. When you build a segment of customers who bought running shoes in the last 90 days, that segment is built on unified individuals. When a flow launches a campaign, the audience comes from here.

Now Linda can see what's missing. The running shoe buyers segment doesn’t exist yet. Before she can build the segment, three things need to be true:

• Purchase data is brought into Data 360 as a data stream.
  
• It’s mapped to the appropriate DMO, such as Sales Order.
  
• The Sales Order DMO is related to the Unified Individual object.
  

Once this foundation is in place, Linda can create the segment and use it in a flow.

Data Graphs in Marketing Cloud Next

Even when data exists in Data 360, it isn’t automatically available in Marketing Cloud Next. A data graph defines which DMO objects and fields are exposed for use in personalization and decisioning. Think of it as a map that tells Marketing Cloud Next what data it can access.

Every data graph starts with Unified Individual as the primary object and connects to related DMOs, such as Loyalty Program Member and Sales Order. Each connected DMO adds its own fields to the graph. For example, the Loyalty Program Member DMO includes the loyalty tier field, giving Linda the data she needs to personalize her campaign and power a decision split.

While data graphs can be built on any DMO, Marketing Cloud Next requires Unified Individual as the primary DMO. The segment driving the flow is also built on Unified Individual, and the two must align.

With the data graph configured, Linda can unlock the capabilities she needs for the campaign.

• Merge fields in emails: Inserting customer-specific values, for example, "Welcome back, Maya!”
  
• Dynamic content blocks: Showing different content to different tier members
  
• Decision splits in flows: Routing customers based on attributes like loyalty tier
  
• Form pre-fill: Auto-populating known customer details
  

Remember Linda's second problem? The loyalty tier field wasn't available for the decision split. The data graph explains why. The loyalty data exists in Data 360 and is mapped to the Loyalty Program Member DMO, however, the loyalty tier field isn’t added to the data graph yet. Until a field is explicitly included, Marketing Cloud Next can't access it. Data existing in Data 360 doesn't automatically make it available everywhere.

Data Access from Salesforce Objects

There's one more layer worth knowing. Flows in Marketing Cloud Next can draw data directly from standard Salesforce objects, such as Contacts, Leads, and Accounts, without going through Data 360.

For example, a flow that uses a Get Records element on the Contact object retrieves data directly from Salesforce core. This allows marketers to incorporate operational data into their flow logic, such as checking whether a customer has an open support case or whether their account status is active.

Here’s a recap of how each component in Marketing Cloud Next pulls data from a specific source.

Understanding these distinctions helps Linda know exactly where to look when data is missing.

Linda's Path Forward

Armed with this understanding, Linda now knows exactly what to do.

1. Verify that running shoe purchase data is ingested and mapped to the Sales Order DMO.
   
2. Confirm the DMO is related to the Unified Individual object.
   
3. Build the running shoe buyers segment in Data 360.
   
4. Verify that the loyalty tier field exists in a DMO.
   
5. Add the loyalty tier object and fields to the data graph.
   
6. Build the email and configure the decision split based on loyalty tier.
   

In this unit, Linda identified that the running shoe buyers segment doesn’t exist yet, and the loyalty tier field hasn't been added to the data graph. Now it's time to fix both. In the next unit, you follow Linda through building the segment, configuring the data graph, and activating the audience in Marketing Cloud Next.

Resources

• Salesforce Help: Data Objects in Data 360
• Salesforce Help: Data Graphs