Tag: Data Cloud

Salesforce has integrated Data Cloud capabilities into its sandbox environments, allowing developers to build, test, and deploy Data Cloud-powered applications without impacting live production systems. This integration enhances the development process by providing a secure, isolated setting for innovation.

Availability and Access

General Availability: As of November 2024, Data Cloud in Sandbox is generally available. To utilize this feature, customers need to purchase the new Data Cloud Sandbox SKUs. After acquisition, creating a new sandbox or refreshing an existing one will enable Data Cloud functionalities within the sandbox environment.
Supported Sandbox Types: Data Cloud is supported across all sandbox types, including Developer, Developer Pro, Partial Copy, and Full Copy. This flexibility allows teams to choose the sandbox type that best fits their development and testing needs.

Features and Capabilities

In the sandbox environment, developers can:

Test Data Streams and Models: Integrate various data sources into Data Cloud, configure data models, and ensure accurate data mappings and transformations.
Configure AI and Analytics Tools: Set up and test AI models within the sandbox to deliver precise insights and predictions. This includes creating new models in Model Builder or importing models from platforms like Databricks, Google Vertex AI, and Amazon SageMaker.
Prototype Data Cloud-Triggered Automations: Develop and test new automations triggered by changes in Data Cloud tables, ensuring seamless integration with existing workflows.

Considerations

Data and Authentication: While Data Cloud configurations from the production environment are replicated in the sandbox, data and authentication information are not. After creating the sandbox, connections must be reconfigured, and authentication information provided to ingest data into the Data Cloud sandbox.
Usage and Billing: Data Cloud usage in sandboxes consumes credits and multipliers from the production org’s Data Cloud credit cards, covering categories such as Data Service, Storage, and Segmentation and Activation. This ensures that sandbox usage is accounted for in overall consumption.

By integrating Data Cloud into sandbox environments, Salesforce provides a robust platform for developers to innovate and test new features securely, ensuring that all components work cohesively before deployment to production.

We’ve been talling about Data Cloud and new features in the Salesforce Sidekicks Podcast (in Italian).

Sources: Salesforceblogger.com, Salesforce Dev Blog

🇮🇹 Salesforce Sidekicks EPISODE 11: Data Cloud – Tips, Tricks and More

By Pietro Piga

On April 2, 2024

In Podcast

ℹ️ Di cosa si tratta? / What’s this all about? Salesforce Sidekicks

In questo episodio vediamo meglio cos’è Data Cloud con l’aiuto di Luca Miglioli, un Solution Architect che ha preso parte al primo progetto di implementazione italiano di Data Cloud.

Insieme a Luca capiamo cos’è Data Cloud, cosa non è, quali sono i suoi punti di forza e alcuni consigli da chi l’ha già implementato per dare quel tocco in più che non troverete da nessun’altra parte 😎

Spoiler: il Team si allarga per mettere ancora più energia nei contenuti che ci chiedete e nell’episodio vi diremo con chi 👂

Inoltre Enrico lancia un concorso a premi e inaugura l’angolo delle letterine 🤩📧

Buon ascolto!

TrailblazerDX 2024: Recap, Keynote, and Key Announcements 📢

By Luca Miglioli

On March 12, 2024

In Post

Missed the two-day event packed with the latest from the Salesforce world?

Worry not!

Here’s a summary of all the important announcements!

Einstein Copilot — the new application that enables natural language interaction with Generative AI on Salesforce is finally GA! Configurable, customizable, and integrable with any data or automation present on the platform (Flow, Apex, etc.), this virtual assistant can be integrated into any business process and assist users in every operation.

Einstein 1 Studio — a set of low-code tools becomes available that allows you to customize Generative AI capabilities on your CRM. In particular, Einstein 1 Studio includes features such as, in addition to the Einstein Copilot Builder, Prompt Builder for creating and activating custom prompts (text-based instructions) in your workflow, and Model Builder, where users can create or import a variety of AI models to their liking.

Data Cloud — from an AI perspective, not only will the solution’s architecture be expanded with the implementation of a new feature called Vector Database, which will allow you to unify unstructured or non-structured data (such as PDFs, images, emails, etc.) within your CRM and make them available to train Einstein AI, but you will also be able to bring your own AI model or integrate it with an existing one thanks to the BYOM (Bring Your Own Model) functionality, thus bringing data from external systems as well. Thanks to the ability to manage access to Data Cloud metadata and data through Data Spaces, it is now possible to integrate the latter more easily with the CRM using fields and related lists directly from Data Cloud, in addition to the ability to materialize a certain subset of data through Data Graph to make it available in real-time for queries and other operations.

Einstein for Developers — numerous new features for Salesforce developers, who will be able to use AI in their work: from assisted autocompletion while writing code, to translating natural language requirements into code, to automatic generation of test cases, to code analysis.

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When Salesforce is life!