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Import and Map Data

Learning Objectives

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

  • Sign up for a special Developer Edition org.
  • Create a data stream using a file-based source.
  • Map ingested fields to the correct target object and data types.

Sign Up for a Developer Edition with Data 360 and Marketing Cloud Next

To complete this challenge, you need a special, limited-time custom playground that contains Data 360 and Marketing Cloud Next.

  1. Click Create Playground.
  2. Your new org is automatically attached to your Trailhead account.
  3. Make note of your org's expiration date and complete this badge before then.

You're now ready to follow along in your new playground and complete the steps in this unit. At the end of the unit, select Check Challenge to Earn 500 Points to verify your work.

Create a Data Stream

Time to get Cloud Kicks's loyalty data into Data 360.

A data stream is a configured connection that brings external data into Data 360. After it's set up, the data stream runs on a schedule you define, so your segments, flows, and personalizations stay current as data changes.

As part of setting up the stream, you choose a primary key for the incoming data. The primary key uniquely identifies each record within the incoming data, ensuring every row in the DLO can be distinguished from every other row. For this data stream, you select Member ID as the primary key because it’s a stable, dedicated identifier. Unlike an email address, it won’t change if a customer updates their contact information.

In this unit, you work with the CSV file we mentioned earlier that’s exported from the Cloud Kicks loyalty platform.

Note

Uploading a file is a form of batch ingestion where you're bringing in a snapshot of data at a specific point in time. When the loyalty data changes, someone exports a new file and runs the stream again. Marketing Cloud Next also supports direct connections to source systems, where data flows in continuously. Either way, the activation steps are the same.

Before creating the stream, download the CSV file from the org.

  1. In your special playground, select App Launcher, and then enter and select Files.
  2. Select Show more actions next to Cloud_Kicks_Loyalty_Data, and select Download.

Note where the file is saved on your computer.

Ready to create the stream?

  1. Select App Launcher, and enter and select Data Streams.
  2. Select New.
  3. In the Other Sources section, select File Upload.
  4. Select Next.
  5. Select Upload Files to select it from your computer.
  6. Select the file from your computer and click Open.
  7. When the upload is complete, in the Properties tab, select Member ID as the Primary Key.

The New Data Stream window where you define the primary key.

  1. Select Next.
  2. Specify these details.
    • Data Stream Name: Cloud Kicks Loyalty Data
    • Data Space: default
  3. Select Deploy.

After the job runs, check that Data Stream Status is Active and Last Run Status is Success. If it shows Failed or stays in Pending, here are a few things to check.

  • Confirm the CSV file is formatted correctly and contains no empty required fields.
  • Verify the data stream is pointed at the correct file location.
  • Check that the field types in your mapping match the data in the file. For example, a text value in a field mapped as a number will cause the job to fail.

After you've made corrections, rerun the job and confirm the status updates to Success. When it does, the raw values land in a DLO, but Data 360 doesn't know what they mean yet. Platinum is just text, and 8500 is just a number. That's where field mapping comes in.

Map Ingested Fields

Imagine you just moved into a new apartment and every box is labeled Stuff. You know everything is in there somewhere. But finding anything is a nightmare. Mapping is how you label the boxes. It connects each DLO field to a data model object (DMO), giving every value clear meaning. Platinum becomes a loyalty tier, and 8500 becomes a points balance.

Before mapping individual fields, you select the DMOs that the Cloud Kicks fields belong to. Here's how they break down.

  • First Name and Last Name map to the Individual DMO.
  • Email Address maps to the Contact Point Email DMO. Because Email Address is a contact point, this DMO is specifically designed to hold it. It's what Data 360 uses during identity resolution to match records to unified profiles.
  • Loyalty Tier and Points Balance belong in a Loyalty Program Member DMO, but for this module, you map them to custom fields on the Individual DMO as a practical alternative.
  • Member ID plays a special role. It maps to multiple DMOs as a linking field, connecting records across objects.

Now that you know where each field is going, start by selecting the DMOs you need.

Select the DMOs

In this section, you add the Individual and Contact Point Email DMOs to your data stream so that you have target objects ready for mapping.

  1. In the Data Mapping section of the Cloud Kicks Loyalty Data data stream, select Start.

The Cloud Kicks Loyalty Data data stream page where you add an object to begin mapping.

  1. In the Data Model entities section, choose Select Objects.
  2. In the Standard Data Model tab, search for and add Individual and Contact Point Email by selecting Addfor each one.
  3. Select Done.

Data 360 automatically maps fields when the column name in your DLO exactly matches a standard field name in a target DMO.

Data 360 automatically maps fields with common column names.

Email Address, First Name, and Last Name are all auto-mapped for exactly this reason.

Map Fields to the Contact Point Email DMO

The Email Address field automatically maps to the Email Address field of the Contact Point Email DMO. This is the actual email value, such as john@example.com. Complete two additional mappings here.

  • Email Address > Contact Point Email ID. This is the primary key of the Contact Point Email DMO. It uniquely identifies each contact point email record within the data model.
  • Member ID > Party. This relationship field links the contact point email back to the Individual it belongs to. Think of it as a bridge that connects an email address to a person.

Here’s how you map the fields.

  1. In the Contact Point Email DMO section, select Unmapped.
  2. In the Cloud Kicks Loyalty Data section, select Email Address. Then in the Contact Point DMO section, select Contact Point Email Id. As you hover over the fields, you’ll notice the connector.
  3. Similarly, click Member ID and map it to the Party field.

Map Fields to the Individual DMO

The Individual DMO needs a unique identifier to represent each person as a record within the data model. Mapping Member ID to Individual ID serves that purpose. When identity resolution runs and creates a Unified Individual profile, it can trace that unified profile back to the originating loyalty record.

  1. In the Individual DMO section, select Unmapped.
  2. In the Cloud Kicks Loyalty Data section, select Member ID. Then in the Individual DMO section, select Individual Id.
  3. Select Save before creating fields for the remaining mappings.
  4. In the Individual DMO section, select Unmapped, and select Add New Field.
  5. Specify these details.
    • Field Label: Loyalty Tier
    • Data Type: Text
    • Select Save

The Add New Attribute window where you enter details of a custom field.

  1. Repeat step 4 to add another field with the following values.
    • Field Label: Points Balance
    • Data Type: Number
    • Select Save

Next, map the loyalty fields to the custom fields.

  1. In the Cloud Kicks Loyalty Data section, select Loyalty Tier. Then in the Individual DMO section, select Loyalty Tier.
  2. Similarly, map the Points Balance fields.
  3. Select Save & Close.

The Cloud Kicks Loyalty Data Mappings page with the mapped fields.

The loyalty data is now mapped and structured in Data 360. In this unit, you completed the first two stages of the Data 360 activation process. You created a data stream that brought the Cloud Kicks loyalty data into a DLO, and you mapped each field so Data 360 understands what every value represents. The data is structured and ready, but it isn't yet connected to the right people. Data 360 can access a loyalty tier and a points balance, but it doesn't yet know which customer profile they belong to. That's the job of identity resolution, and it's what you tackle in the next unit.

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