Even though data is the backbone of better decision-making, the disconnect between data products and business platforms is proving to be detrimental, making Salesforce Data Cloud important since it unifies data sources for enhanced commercial insights.
By creating a value add layer on top of the existing data infrastructure, Salesforce Data Cloud avails richer analytic components through the integration of standalone data products, boosting insights in broader areas, such as sales and marketing, according to Muralidhar Krishnaprasad (pictured), exeuctive vice president of software engineering at Salesforce Inc.
“We are trying to bridge the gap between the CIOs running these data platforms with really the line of business users like our sales, service marketers and others, and really untrap the data in all of these and make it usable to all of these business users, and that’s really the fundamental key point with Data Cloud,” Krishnaprasad said. “Data Cloud lifts all the boats … you can connect it very easily and then every single investment you’ve done with your Snowflake, with your Databricks or Azure, et cetera, is now immediately valuable to your business users.”
Krishnaprasad spoke with theCUBE Research’s George Gilbert at the Supercloud 7: Get Ready for the Next Data Platform event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how Salesforce Data Cloud boosts business insights for optimal results.
How metadata fits into the Salesforce Data Cloud picture
Since metadata harmonizes and normalizes enterprise data, it enables standardization and semantic understanding in Salesforce Data Cloud. This is made a reality through the incorporation of a metadata layer, enabling the inclusion of any type of data from batch streaming to real-time information, Krishnaprasad pointed out.
“If you look at almost every enterprise in the world, there’s no one standardization of schema or metadata or anything,” he stated. “With Data Cloud, we are able to then create that metadata, harmonize it so you can actually speak the same language across all of your application surfaces. We also have something called Zero Copy Partner Network, where we expand it to be able to just point to the existing data warehouses and lakehouses.”
With the help of metadata, Salesforce Data Cloud is able to create a semantic later for enhanced business understanding. The Zero Copy Partner Network also comes in handy in heightening data governance since teams can easily access information from different locations, without having to copy or move data across platforms, according to Krishnaprasad.
“Metadata offers that powerful foundation for us to normalize and harmonize across all of your enterprise data,” he noted. “The Zero Copy Partner Network helps us then reuse a lot of that data and the metadata that’s sitting in existing systems very, very easily.”
Given that the metadata harmonizes all the data by delving deeper into vital details, such as key performance indicators and individual clients, developers are able to build an application that reflects the business. This makes Salesforce Data Cloud offer comprehensive business insights, such as how a marketing campaign will perform, according to Krishnaprasad.
“Just last month, one of the largest automotive vendors in Europe did this thing where they had data in their sales cloud, which was talking about their customers,” he explained. “Within a matter of weeks, the business users, the sales people in their automotive company, were able to create a predictable lead score using Data Cloud where they brought all that digital signals from their website, backend implementations and sales cloud customer information.”
Generative AI in Salesforce Data Cloud
Salesforce Data Cloud is not averse to technological innovations because this platform uses gen AI to simplify data engineering tasks by automating data transformations and indexing metadata. This is made a reality by incorporating the AI for data and data for AI concepts, Krishnaprasad stated.
“We all know how important data is for AI and that it is used in applications,” he said. “When we talk about AI for data, these are gen AI to be able to help with all of your data work. How could we create transformations much more easily? Let’s take a simple example, like a marketing campaign. If I ask, ‘Find me all the segments of adults living in New York City who have purchased something?’ This probably will touch 15 different tables. We look at GenAI as really helping with that task quite a bit.”
As an active platform, Salesforce Data Cloud harmonizes, unifies, augments and analyzes data using the existing data infrastructure. As a result, it supports a richer class of applications beyond analytic data products, such as machine learning models and business intelligence dashboards, according to Krishnaprasad.
“It’s not just about passive data; it’s really about making it active so that it can now trigger actions for all of your business audiences,” he stated. “It’s an active platform. What we mean by that is it’s not a traditional platform where you just look at a dashboard. It’ll generate alerts, flows and trigger changes so that you can actually react to all of your data and insights. We can enrich your overall profile of what the user is doing across your business.”
Stay tuned for the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of the Supercloud 7: Get Ready for the Next Data Platform event.