Note that some of the features discussed below might still be on the roadmap and not GA yet.
In the evolving landscape of technology, Salesforce Data Cloud has undergone a remarkable year of updates. Marking a shift from its former identity as Customer Data Platform (CDP). Beyond a simple name change, this transformation signifies a broader focus that extends well beyond marketing segmentation. Now known as Salesforce Data Cloud, this platform offers exciting possibilities for various teams within a company, moving beyond marketing to empower sales, customer care representatives, and more. The business side of your organization can now harness the full potential of data cloud for smarter decision-making and improved efficiency. Underlining this evolution are the introduction of intriguing new AI capabilities. Expanding beyond traditional data processing to provide predictive analytics and personalized customer experiences. The power of intelligent insights is now at your fingertips.
Addressing user needs
In addition, Salesforce Data Cloud has been attentive to user feedback, incorporating essential features that clients have longed for. The inclusion of data cleansing tools ensures data integrity, addressing a common concern among users. Sandbox support has been seamlessly integrated, providing a controlled environment for testing and development.
Another addition is the introduction of Account Resolution, like identity resolution but tailored specifically for accounts. With the need for real-time insights, Salesforce Data Cloud pushed it’s real-time capabilities to milliseconds rather than the previous 2-3 minutes. In the next parts, we’ll explore these improvements in more detail, highlighting how they can boost your business.
Data Cloud is built on Hyperforce, the new Salesforce infrastructure architecture based on the consumption of public cloud services. This approach ensures a stronger and easily scalable platform, as Salesforce no longer has to handle the details of physical resources. In this updated setting, the platform transforms into a hyperscale data platform that excels in efficiently managing large volumes of data, offering your business a solid foundation for growth and innovation.
Unlocking the power of AI
Einstein Studio makes it easy for data science and engineering teams to manage and deploy AI models more efficiently, and at lower cost. Through this Bring Your Own Model (BYOM) solution, customers will be able to use their custom AI models alongside turnkey LLMs provided through Einstein GPT, enabling them to deliver comprehensive AI fast. Currently only Amazon SageMaker from Amazon Web Services is available but Google cloud’s Vertex and Databricks are on the roadmap as well.
When you don’t have your own model yet, the introduction of the Prediction Calculator in Einstein Studio is a noteworthy development. This user-friendly tool allows you to create personalized predictions, such as forecasting churn or estimating Lifetime Value (LTV) spend, all with simple clicks and without the need for coding.
Leveraging the unified data from the Data Cloud not only supercharges your AI capabilities but also serves as a valuable resource to feed your custom models, ensuring they are enriched with a comprehensive dataset.
The Data Cloud Vector Database is like a supercharged brain for AI, making it smarter without needing constant adjustments. It takes all sorts of information from your business, like emails, PDFs, and purchase history, and combines them into a powerful tool for AI, automation, and analytics across Salesforce applications. This not only boosts the value you get but also makes your business processes more efficient. The upgrade to Einstein Copilot Search makes it a really smart assistant that can understand complex questions and find answers from different sources, including unstructured data.
Already have your own data lake? Make use of the Zero Copy Bidirectional Integration.
Bring Your Own Lake (BYOL) Data Sharing allows joint customers to enhance the value of their Salesforce data by combining it with enterprise data in Snowflake, simplifying data conversion into actionable insights. Now introduced is the BYOL Data Federation, facilitating access to Snowflake data within Salesforce Data Cloud for bidirectional data sharing. This approach, labeled as Zero-ETL, eliminates the need for complex Extract, Transform, Load (ETL) processes, ensuring real-time access to up-to-date data with enhanced security and governance. For BYOL other lakes like BigQuery, Redshift and Databricks are on their roadmap and will be available soon.
As you’ve explored the latest Data Cloud updates, we hope you’ve found valuable insights into the enhanced capabilities that can transform your business. If you’re interested in implementing Data Cloud for your organization, we’re here to chat. Our team is ready to discuss how these advancements can specifically elevate your operations. For a deeper dive into the marketing capabilities of Data Cloud, check out our dedicated article on leveraging its power for marketing strategies.
