Mastering Salesforce Data Cloud Deployments with Data Kits

When you’re deep into building magic with Salesforce Data Cloud — whether that’s crafting powerful identity resolution rules, tuning calculated insights, or slicing your data into sharp segments — eventually, you’ll hit a wall: “How do I move all of this safely to another environment?” Join us to learn about Salesforce Data Cloud Deployments with Data Kits.

Table of contents

What Are Data Kits?

Think of a Data Kit as a metadata suitcase for Salesforce Data Cloud. It doesn’t carry customer data — it carries your configuration: the brainwork, the logic, and the structure of your data intelligence. It lets you version, migrate, and deploy Data Cloud configurations across sandboxes and production environments in a structured, reliable way.

Standard Data Kit vs DevOps Data Kit

Salesforce offers two flavors of Data Kits depending on your use case:

Standard Data Kit

Ideal for interactive deployments via the UI.
Supports manual deployment using Change Sets.
Meant for smaller, sandbox-oriented configuration movements.
Less suited for automation or version control.
Limited logging and visibility — not ideal for tracking changes over time.

DevOps Data Kit

Designed for CI/CD workflows and automation.
Allows downloading of manifest files.
Fully compatible with Salesforce CLI and package.xml-based deployments.
Enables version-controlled deployment via source control tools like Git.
Supports integration with external DevOps systems like Jenkins, GitHub Actions, and Azure DevOps.
Enhanced auditability and rollback through versioning.
Improves team collaboration by aligning Data Cloud deployments with existing DevOps pipelines.
Reduces deployment risks by promoting tested artifacts through multiple environments.
Enables repeatable, deterministic deployments, making it easier to detect drift and inconsistencies.
Facilitates change tracking and compliance auditing, crucial for regulated industries.

A single DevOps Data Kit can be re-used across multiple stages (Dev → QA → UAT → Prod), making it the preferred option for teams focused on compliance, velocity, and repeatability.

Data Kits Support These Content Types:

Data Streams – Source data connections
Data Model Objects (DMOs) – Your structured schema
Identity Resolution Rules – Matching and unification logic
Segments – Filtered audiences built from your data
Calculated Insights – Metrics like LTV, frequency, churn, etc.
Unions – Combined datasets across sources
Activations – Destination endpoints for marketing or external apps
Transformations – Data reshaping logic
Data Bundles – Logical grouping of config items

Deployment Order Matters

Data Cloud configurations have dependencies, so the publishing sequence is critical. You can’t publish a calculated insight before its referenced DMO exists. Salesforce handles this behind the scenes for most deployment methods — but if you’re crafting your own manifest, you’ll want to respect the order:

Data Streams
DMOs
Identity Rules
Insights
Segments
Activations, Unions, etc.

Deployment History

A place to view the deployment status and deployment errors. A few sample errors are shown in the screenshot below.

Three Powerful Ways to Deploy Data Kits

Salesforce offers flexibility depending on your comfort level and workflow. Here’s how you can get your Data Kit from dev to destination:

1. Change Set Deployment (Clicks, Not Code)

For the admin who loves the UI, this is the easiest path:

Create your Data Kit by adding all the required components and the publishing sequence
Create your changeset like usual and look for the component type called ‘Data Package Kit Definition’

PS: Don’t forget to click ‘View/Add Dependencies’. Adding just the data kit doesn’t add the components inside it.

Great for smaller teams or one-off deployments.

2. Download Manifest + Salesforce CLI (Automated & Repeatable)

For DevOps teams or advanced users who love Git and CI/CD:

From the Data Kit UI, click Download Manifest — you’ll get a package.xml
Deploy with the Salesforce CLI:

sf project deploy start –manifest manifest/package.xml –target-org your-sandbox

This method is version-controllable, repeatable, and ideal for release pipelines.

3. Compose Your Own package.xml in VS Code (Power User Mode)

Want pinpoint control? You can manually write your own package.xml with exactly what you want to deploy:

<?xml version="1.0" encoding="UTF-8"?>
<Package xmlns="http://soap.sforce.com/2006/04/metadata">
    <types>
        <members>MessagingSession_Home</members>
        <members>SalesforceDotCom_Home</members>
        <name>DataKitObjectDependency</name>
    </types>
    <types>
        <members>JoinMStoConversation</members>
        <members>MessagingSession_Home</members>
        <members>SalesforceDotCom_Home</members>
        <name>DataKitObjectTemplate</name>
    </types>
    <types>
        <members>MIAW_Chat_Transcript</members>
        <name>DataPackageKitDefinition</name>
    </types>
    <types>
        <members>MIAW_Chat_Transcript_1743688369456</members>
        <members>MIAW_Chat_Transcript_1743688371158</members>
        <members>MIAW_Chat_Transcript_1743688371409</members>
        <members>MIAW_Chat_Transcript_1743688397273</members>
        <members>MIAW_Chat_Transcript_1743688410331</members>
        <members>MIAW_Chat_Transcript_1743688410951</members>
        <name>DataPackageKitObject</name>
    </types>
    <types>
        <members>MIAW_Chat_Transcript</members>
        <members>Salesforce_Home</members>
        <name>DataSource</name>
    </types>
    <types>
        <members>MIAW_DataStreams</members>
        <name>DataSourceBundleDefinition</name>
    </types>
    <types>
        <members>MIAW_Chat_Transcript</members>
        <members>MessagingSession_Home1</members>
        <name>DataSourceObject</name>
    </types>
    <types>
        <members>MessagingSession_Home_1743688371181</members>
        <name>DataStreamTemplate</name>
    </types>
    <version>63.0</version>
</Package>

Deploy it with CLI or plug it into your automated pipeline. This is DevOps gold.

Which Path Is Right for You?

Method	Best For	Tools Needed
Change Set	Admins, quick tests	Salesforce UI
Manifest + CLI	DevOps, versioning	Salesforce CLI, Git
Manual package.xml	Fine-tuned deployments	VSCode, CLI

Final Thoughts

Data Kits are a game-changer in managing Data Cloud deployments. Whether you’re working solo or across a multi-org enterprise, they give you the structure, control, and flexibility you need to move fast without breaking things.

And best of all? You choose how to use them — clicks, code, or full CI/CD.

Mastering Salesforce Data Cloud Deployments with Data Kits

What Are Data Kits?