Great news for developers building, testing, and shipping Data Cloud-powered apps: Data Cloud is now generally available (GA) in Salesforce Sandboxes! Having Data Cloud functionality in sandboxes gives you the flexibility to build and test new Data Cloud projects in the same way that you test other Salesforce releases and projects.
By refreshing your existing sandboxes or spinning up new ones, you can take full advantage of Data Cloud’s capabilities in a secure, isolated setting. This allows developers and IT teams to:
- Test changes in a secure environment using your real Data Cloud data streams
- Provide a training environment for new users
- Test AppExchange packages or integrations
- Isolate Data Cloud customization and development work from your production environment until you’re ready to deploy changes
What this means for developers
Salesforce Sandboxes have long been integral for safe development and testing, allowing teams to work with configurations and data in an isolated environment that mirrors production without any risk to actual business operations.
With the inclusion of Data Cloud, sandboxes now empower teams to innovate with confidence by working in environments that accurately reflect production.
Being able to test Data Cloud integrations, automations, and workflows in real-world scenarios before deployment helps developers achieve DevOps best practices. It also ensures harmonious operation across your entire Salesforce ecosystem, from Customer 360 data unification to advanced insights and analytics.
With the ability to build and test Agentforce in sandboxes, teams can develop and refine intelligent workflows and automations, enhancing productivity and delivering more personalized, data-driven experiences before they go live.
Example capabilities you can now build, test, and deploy in a sandbox
Test Data Cloud rigorously in Sandboxes, across production capabilities and use cases.
Data streams, models, and calculated insights
Integrate diverse data sources into Data Cloud, testing data import, modeling, and federated zero copy access to other lakes and warehouses, and ensure accurate mappings and functional data transformations. You can even create and explore new calculated insights across your CRM without disrupting operations.
Agentforce
Test your Agentforce Actions and Skills thoroughly, including ones powered by Data Cloud data. Run performance and output checks on actions that call Data Cloud data streams before promoting new Agentforce or Data Cloud features to production.
AI and Analytics
Configure and test AI tools within a sandbox to verify that they deliver precise insights and accurate predictions. Create new models in Model Builder using training data that you stream in, or import models from existing ML platforms, such as Databricks, Google Vertex AI, and Amazon SageMaker, then validate them with your business analyst teams.
You can also create a new search index and design search retrievers in Prompt Builder that use semantic search to unlock insights from unstructured content. You can even experiment with new reports on Data Cloud data before delivering them to your end users – all in isolation from existing business processes.
Data Cloud-triggered flows
Prototype, test, and deploy new automations that are triggered off of changes to Data Cloud tables. Use zero copy integration to bring in data from existing lakes or warehouses (like inventory data from Google BigQuery), and see how that can be used, for example, to fuel a backorder notification to a customer when an item is in stock.
Development teams can scaffold new Data Cloud-triggered automations alongside existing flows and flow orchestrations to see how they can deliver end-to-end process automation using all of their critical business data, then validate their work with business users before deploying to production.
Sales data optimization
Connect, harmonize, and fine-tune diverse data sources to predict customer behaviors and key metrics, such as the likelihood to close and revenue generation. In Partial Copy and Full sandboxes, your CRM data will automatically be replicated, making it immediately available for use with Data Cloud.
This allows for the creation and testing of automated sales workflows, like opportunity routing and forecast updates, and personalized engagements, thus enhancing decision-making and increasing efficiency through AI-driven insights utilizing your actual data.
Enhanced customer service
Increase customer satisfaction and agent productivity by creating a comprehensive view of the customer. Similar to sales data, your service data will be automatically replicated in your Partial Copy and Full sandboxes.
This allows your teams to implement intelligent automation to increase case deflection and CSAT, and provide customer service agents with proactive alerts to assist their customers effectively. You can also develop and test personalized recommendations for customer interactions based on service history, transaction history, product telemetry data, and more.
Personalized marketing
Create new segments – including through the use of generative AI – to explore untapped audiences that your marketing teams can target, and do so using web interaction data or product usage data that may live in another data store, such as Google BigQuery.
Security and compliance
Detect potential vulnerabilities and compliance gaps while testing in the sandbox, then use this information to address the underlying issues without exposing the live system to risks, thus safeguarding your data and maintaining trust. Use Data Mask to continue masking your CRM data prior to ingestion into Data Cloud, ensuring critical PII stays secure.
Training and testing
Train new team members and help familiarize them with Data Cloud in a secure, mirrored environment, ensuring faster time to adoption and value. You can also enable pre-release access for your key stakeholders, such as a customer service team that will be using Data Cloud data to deliver proactive support, and then iterate fast on their feedback before wider release.
The use cases for exploring and verifying Data Cloud capabilities in a sandbox extend beyond the ones listed here to any scenario you might imagine – with the common thread being that a Data Cloud implementation or customization can be tested, extended, and delivered in a secure, isolated environment.
Promote from sandbox to production with enhanced DevOps
Once testing is complete and configurations are finalized, promoting the changes from a sandbox to the production environment is streamlined through tools like change sets, Salesforce CLI, Metadata API, and DevOps Center, utilizing the new DevOps Data Kit.
The DevOps Data Kit helps you collect and sequence Data Cloud configuration for deployment from sandboxes to production, or to another environment. A data kit offers a simpler DevOps process for migrating complex Data Cloud metadata.
Regardless of which option you choose, admins and developers now benefit from a simplified Data Cloud release management process, allowing your teams to deploy validated configurations with greater confidence and ease. Having a DevOps process for Data Cloud will help you minimize deployment risks, and accelerate the pace at which your organization can respond to changing business needs.
Sandboxes fit into Data Cloud delivery cycles in eight stages:
- Discovery and Prioritization
- High-Level System Architecture
- Field-Level Data Mapping
- Data Ingestion, Modeling Sample
- Expanded Ingest, Configuration
- Activation & Orchestration
- Test, Remediate, & Train Users
- Pre-prod Staging, then Launch!
How to enable Data Cloud in sandboxes
All Data Cloud features are fully functional in sandboxes. Speak with your Salesforce AE to provision Data Cloud in sandboxes for your org. Once you’ve done that, follow these steps to enable Data Cloud in your sandboxes.
Step 1: Create a sandbox
- Create a sandbox by following the steps in the Help article, Create a Sandbox.
Step 2: Turn on Data Cloud in the sandbox
Log into your sandbox org. From Data Cloud Setup, click Get Started. Setup can take a few minutes. For more information, see Turn On Data Cloud.
Note: If your sandbox was created prior to August 1, 2024, it will require a refresh in order for Data Cloud to provision. If the sandbox was created after Data Cloud is provisioned and after August 1, 2024, then you can use the License Match tool to enable Data Cloud in your sandbox.
Step 3: Configure connections
When you create a Data Cloud sandbox, connections are replicated, but the authorization data isn’t, so the connections in the sandbox org have a status of Inactive.
- Finally, activate each sandbox connection and provide the authorization information to bring data into the sandbox.
Learn more about the development cycle for Data Cloud by watching our on-demand webinar.
Conclusion
Data Cloud in Salesforce Sandboxes represents a major step forward in our commitment to providing secure, robust, and flexible tools that meet the complex needs of developers and IT teams.
Whether you’re configuring a data model or testing new Data Cloud-triggered flows, Sandboxes offer a powerful platform for innovation without compromising the stability of your production systems. Stay tuned for further updates, detailed guides, and more as we continue to expand and enhance this exciting capability.
Resources
- Learn more about Salesforce Data Cloud
- Learn more about Salesforce Sandboxes
- Learn more about Agentforce
About the authors
Margot Tollefsen is a Product Marketing Manager at Salesforce on the Agentforce team focused on technical marketing. Alongside her role in product marketing, she is passionate about empowering Indigenous communities with digital tools and technology.
William Yeh is a Senior Director of Product Management at Salesforce on the Data Cloud team, where he leads platform integration and extensibility initiatives. He is passionate about building SaaS and data platforms, and empowering admins and developers.