Admins are being tasked at a growing rate to integrate with more sources of information to tie back to their Salesforce implementations. You might be hearing a lot of questions about Data Cloud, like how it can help with modern integrations and where it fits into Einstein and artificial intelligence (AI). The good news is that whether you manage a single org or juggle a complex set of systems, Data Cloud can help. Let’s break down how.
Data Cloud is a solution to connect, harmonize, and act on data by creating a unified way to view multiple resources that can be treated like any other first-party data on a Salesforce org. With Data Cloud, you can unify your data without building complex data pipelines, easily take action on unified data across every Salesforce Cloud, and enable trusted AI solutions powered by your data. Data Cloud does this by creating near real-time connections that allow Salesforce to treat connected data like it normally works with standard or custom objects. This removes redundancy across multiple places and provides your own custom data lake to work with using the Salesforce tools you already know.
Salesforce provides a broad library of out-of-the-box configurable connectors to popular data sources like Amazon S3, Databricks, Snowflake, and Microsoft Azure. It also provides a CRM connector that can be used with related orgs within your implementation or the very same org you’re already on. Alongside the Salesforce CRM connector are other Einstein 1 Platform connectors like Marketing Cloud and Heroku. Data Cloud allows you to combine data from these various sources into a standard format that can be surfaced in Salesforce.
Connecting Data Cloud to different types of systems is a fairly unique process compared to what’s normal within Salesforce setup, notably since Data Cloud is trying to sync with an array of sources that have different means of authenticating to the system and handling data. There are a few different ways to make these connections — check the documentation for the specific connector and keep an eye on this space for more information about the different kinds and how they work.
Once you have a connection, you can then set up a data stream to control the flow of data between the source and Salesforce. Behind the scenes, different connections will result in different behaviors in terms of retention and scheduling. Once you’ve created a data stream, check the related settings in Data Cloud to see the options you can control.
Think of your data, whether it’s a single Salesforce org or a whole system of disparate orgs, as a traffic system. You have roads. You have side roads. You have highways with on-ramps and off-ramps. But how do you control that traffic? How can you determine which roads are congested or not being used? More specifically, given a single car, which questions can you ask about that car based on its history on the road? Is it likely to use more gas? Is it going to need a service sooner or later? Are some cars driving a predictable path, and do others stay parked most of the time? Are you going to need more parking or less?
Data harmonization allows data to tie together similar data points and then draw insights and conclusions from it. In the Harmonization Center, you can classify data, identify parent and child relations, and fuse distinct data patterns together. Think of it as an insight-friendly layer placed on top of your data, making it easier to see connections and trends. If you think of data as traffic, then think of Data Cloud as your personal command and control center that gives you a bird’s-eye view, as well as the tools to respond to the flow and monitor the traffic before problems occur.
By harmonizing your data, you take the original source, a data lake object (DLO) in Data Cloud, and add an associated data model object (DMO) to it. You can also employ metrics from the incoming DLO to form a calculated insights object (CIO). For example, you could use a CIO to identify lows and highs in customer trends.
To further help you understand this connected data, Data Cloud offers reports and dashboards to visualize what’s happening, including preconfigured dashboards and the ability to schedule reports.
Managing the distinctions between the various DLOs, DMOs, and CIOs can be complex. Similar but different data points need to be connected in order to start to unify the overall view. Data Cloud gives you the tools to visualize and map these points together; for instance, taking data from a third-party reservation system and mapping it to a DMO.
Once a DMO or CIO is defined, Data Cloud can create custom actions to perform updates, send notifications, and more. As an admin, you can also leverage your existing process automation skills by using Data Cloud with Flow. For example, if your CIO identifies a contact who has a sudden uptick in case activity, a record-triggered flow could kick off to change the status of the contact to reflect, and even create tasks and activities related to the contact, to help form a follow-up plan to keep that contact happy. While it’s true that Data Cloud has its roots as a marketing tool, a customer data platform can be used for any use case that relates to a harmonized DMO or CIO. Not all connectors work with record-based triggers; see the Help documentation for more.
Many use cases can be handled by relatively straightforward flows and not just record-triggered flows. Here’s an example of a screen flow that takes a case record, grabs related DMOs, and then makes it easy to create a follow-up task.
Firstly, Einstein AI relies on Data Cloud to do much of its magic. So, even if you don’t plan on using Data Cloud as a day-to-day solution, tools like Copilot and Prompt Builder will use it behind the scenes to make everything work. And there are features like auditing that rely on Data Cloud’s ability to handle large amounts of fast-moving data to work.
More importantly, though, is that the more complete your data lake is, the more successful your AI tools will be. Let’s take the previous example of a contact with a high risk of cases being formed. What if the customer had submitted product feedback to a third-party system which provides the UI and tracks and aggregates that data? If you try to use Copilot to help determine the cause of the customer’s issues, you’ll give Einstein a serious blind spot as to what the problem might be. The more Einstein is connected to, the smarter Einstein can be.
With Data Cloud, you have the ability to unlock trapped data in your org, surfacing relevant insights and creating a full picture of your customers that all of your users can act on in Salesforce. Whether you’re exploring Data Cloud configurations or bringing Data Cloud insights and related lists into your Salesforce org, now is a good time to start investigating what it can do for your organization.
With Trailhead, you can access a trial of Data Cloud and take it for a test drive. Specialized Trailhead Playgrounds make it easy and free to learn the ins and outs of the product. Also, read 5 Tips for Getting Started for best practices when using Data Cloud.
If you’re more of a visual learner, watch the Data Cloud Fundamentals series from Developer Relations. These are short, easy-to-follow videos from Developer Advocate David Norris.
As of this writing, initial access to Data Cloud is free for Enterprise Edition and above. Some features may require additional licenses, and consuming Data Cloud streams is a consumption token-based system. As always, check with your Account Executive for more information.
Keep an eye on the Salesforce Admins Blog for upcoming content and enjoy these related episodes of the Salesforce Admins Podcast.
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