Expert Corner: Dive into a Demo of Data Cloud with Engineering EVP Muralidhar Krishnaprasad

Right now, businesses like yours are capturing and managing more data than ever: everything from web and mobile clicks to shopping cart data, location data, server data, even telemetry data from connected devices. That’s why we built Salesforce Data Cloud—so #AwesomeAdmins like you could connect, unify, and activate massive volumes of data directly within the Salesforce Platform, at the scale today’s world demands.

With Salesforce Data Cloud, we’re bringing together the flexibility of a data lakehouse and the capabilities of the Salesforce Platform, so that the apps, APIs, metadata, and services you depend on (like Einstein for AI, or Flow for automation) benefit from the scale, latency, and processing power of a public cloud. We’re making it easy to capture all the customer touchpoints that might not have felt accessible in the past, maybe due to volume or storage limitations—like records across multiple Salesforce orgs, or commerce activities from physical and digital stores, or third-party data from advertising technology (adtech) or marketing technology (martech) platforms. The opportunities for admins and devs are endless.

So how does it all work?

• Data Cloud starts by ingesting data from a wide range of sources, using prebuilt connectors across Salesforce sources (Sales Cloud, Service Cloud, etc.) and third-party sources (Google, Amazon Web Services [AWS], and more), web and mobile tags, APIs and software development kits (SDKs) for batch and streaming data, and MuleSoft for legacy applications and systems across your business. This is all thanks to Data Cloud’s lakehouse architecture, which makes it capable of processing data at massive scale—petabyte scale—across thousands and thousands of requests per second.
• Data Cloud then gives you the option of refining your data using real-time streaming transformations, or sophisticated batch transformations (what we call recipes), so that the unstructured data you’ve ingested gets structured and validated, and has schema enforced.
• Once the data is refined, Data Cloud enables you to harmonize and unify your data into a single, unified view of every customer, leveraging canonical reference models built right in. This step is crucial, as there tends to be tremendous variety in schema across enterprise data: A Contact to your sales and service teams might be recorded as a Subscriber by marketing, or a Profile by commerce; to stitch these identities and accounts together ensures that you know it’s the same person who opened your emails, spoke to a service rep, and met in-person with someone from sales.
• Now with this unified, harmonized view, you can run analysis and predictions on data across the enterprise. You can generate incredibly deep streaming and batch insights, leveraging your own tools for AI and business intelligence (BI) as needed.
• But Data Cloud doesn’t stop there, even when most other systems might. Data Cloud goes above and beyond by allowing you to action on the data across Salesforce Customer 360 and our broader app ecosystem—which enables you to take the results of changes in your data streams or events coming in and, say, send it to Flow, or create a new dashboard in Tableau, or trigger a new journey in Marketing Cloud. You can build rich, engaging applications on the Salesforce Platform using the data in Data Cloud, or take advantage of APIs to build completely new applications. The sky’s the limit.

But why tell you all this when we can show you? Click the video below to see an on-demand demo of Data Cloud, courtesy of Muralidhar Krishnaprasad, EVP, Software Engineering.