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You may have heard of this platform, but its purpose can be a mystery to most. The Salesforce Data Cloud is a data engine within Salesforce that combines data from various sources, providing a unified view.
These sources could include anything from CRM systems, data warehouses, external applications, or streaming sources. Data Cloud can read all forms of structured and unstructured data and bring everything together as a trusted source that powers real-time insights, personalization, and automation.
Let’s dive in deeper to explore Data Cloud in Salesforce and how it helps organizations in managing their data.
Salesforce Data Cloud Architecture
Like most Salesforce products, Data Cloud is a cloud computing platform that also serves as a foundation for Customer 360 and Agentforce. It essentially helps you to break down silos and unify all data across enterprises so that you have real-time insights every time. The powerful Salesforce Data Cloud Architecture supports everything that happens on the front end. Here is a look at the architecture:
- Native Salesforce Layer: The most foundational feature of architecture is the Salesforce layer, since the data cloud is built on the platform. It leverages metadata, security, sharing, object schemas, and flows for the unification of data in Salesforce itself.
- External Data Federation: Instead of making you bring in data manually, the data cloud utilizes data federation to mount external tables as virtual objects, enabling real-time access without redundant copies.
- Zero-Copy Integration & Bi-directional Data Sharing: Data Cloud can query external systems with the help of Zero-Copy integration and push back harmonized results. This helps with the real-time integration and accuracy in results.
- Data Graph Engine: Data Graph Engine is a key component in empowering graph queries in tables. This helps in optimizing performance and storing metadata that decouples how data is stored vs. how it’s queried.
- Activation & Integration Layer: Data Cloud uses over 200 pre-built connectors and APIs to push segments, profiles, and insights to other systems like ad platforms, marketing, and ERP.
- Governance, Privacy & Security Layer: With enterprise data, governance is essential. Data Cloud includes features such as AI-based classification of sensitive data, role-based access, encryption, and compliance tools to ensure security.
This modular architecture allows Data Cloud to remain scalable, flexible, and performance-optimized for real-time use. Let’s see how this architecture brings Data Cloud in action.
How Salesforce Data Cloud works?
Data Cloud makes it possible to connect all data, no matter where it comes from or what format it comes in using the back-end architect.
Let’s break down the flow of raw data to actionable insight in Data Cloud:
1. Ingestion / Connectivity
The first step is obviously the ingestion of data from multiple sources or applications like Amazon AWS S3, Meta, Google Ads, etc. You can connect Data Cloud with many external sources using zero-copy connectors. For example, you can query data directly from Snowflake, Databricks, Google BigQuery, and more. All of this can be done without physically copying or duplicating the data.
2. Harmonization / Unification
Once you have gotten your data inside the cloud, the next step is to harmonize this data. Salesforce Data Cloud maps, transforms, standardizes, deduplicates, and aligns various data sources into a common schema. It identifies multiple profiles of the same customer or user to merge into a single profile. This is where the unified customer view comes into play.
3. Data Modeling & Graphs
Since different users will use your data for different purposes, Data Cloud allows you to create data graphs and data models using the graph engine. You can also develop sub-models that are optimized for specific use cases, such as product interactions or service behaviour. It also supports semantic modeling to help your team keep a consistent meaning throughout the organization.
4. Activation / Real-Time Action
The data you have collected so far needs to be useful, and for that, Data Cloud creates unified profiles and segments to activate the data. This means to make it shareable to downstream systems like Marketing Cloud or use in real-time automation like Flows, APIs or connectors. As Data Cloud is natively integrated, it can directly trigger workflows or surface insights as per the required context.
5. Data Sharing & Feedback
Lastly, data cloud works by flowing data back to external systems or data lakes. Through this, the platform can maintain a sync between Salesforce and external data environments while enabling feedback loops. This includes the sharing of data insights via an architecture that supports computing and storage to make data access more efficient.
And that is how Salesforce Data Cloud works to make the import and export of data simpler in Salesforce.
Is Data Cloud a CDP?
This is a question that often comes up when people learn about Data Cloud, and the simple answer is: yes, but with important distinctions.
While Salesforce Data Cloud provides many functions that are commonly associated with a Customer Data Platform (CDP), it is still more than any traditional CDP. Ingesting customer data, identity resolution, unified profiles, segmentation, and activation into downstream systems are some features that resemble a CDP.
But Data Cloud distinguishes itself by its deep integration into the Salesforce metadata model. It supports activation beyond marketing for the entire Salesforce ecosystem.
Originally, the Customer 360 by Salesforce was branded as the CDP, but with expansion into data infrastructure, identity, and AI, Data Cloud underscores its broader scope. So you can think of Data Cloud as a next-gen, composable CDP built for enterprise scale and cross-cloud usage, rather than a pure marketing tool.
Let’s explore the features that make Data Cloud more than just a CDP.
Key Features & Functionalities of Data Cloud
To understand what makes this tool stand out, here are some Salesforce Data Cloud features:
- The Zero-Copy Integration allows you to move data across systems without spending time manually shifting every piece. This reduces duplication, ETL overhead, and latency.
- With the 200+ pre-built connectors, it can seamlessly integrate with systems like SAP, Shopify, Zendesk, Workday, plus SDKs and APIs for custom sources.
- The identity resolution feature in Data Cloud helps in transforming scattered data into a single schema, all while deduplicating and merging identities for a unified profile view.
- The semantic modeling and metrics allow you to define as well as share business metrics, such as lifetime value or engagement score, across teams to maintain consistency.
- It utilizes triggered flows and automation based on real-time updates or calculated insights to send alerts, update records, etc.
- It works with AI to enrich data, score propensities, and power predictive models, giving AI agents the context to act with insight.
Salesforce Data Cloud Benefits
Now that you know everything about data cloud, here are some benefits that organizations enjoy while using the platform:
- You get a 360° view of each customer across all touchpoints, which improves insights and decision-making.
- As it provides you with real-time data through flows and APIs, you can easily access context for relevant experiences.
- Since there is only a single source of all data collected through various sources, all organizational teams use the same semantic models and metrics.
- The architecture of data cloud allows scaling across large datasets easier whether it is structured or unstructured data.
- Traditionally CDPs are marketing-centric but Data Cloud’s closer integration with the broader Salesforce ecosystem allows sales, service, commerce, and analytics teams to benefit equally.
- Because Data Cloud is positioned as a foundation for AI, businesses can ground their predictive and generative models in trusted, unified data.
Final Thoughts
Salesforce Data Cloud is an enhanced CDP platform that goes beyond saving data and makes it useful. It unifies and activates information in a single system to act as a central nervous system.
With the integration of AI across the Salesforce ecosystem, it plays a major role in enabling real-time insights, consistent logic, and automated actions in an organization. To improve the agility, insight, and customer experience, it is an ideal Salesforce native platform. With the adoption and necessity of this platform, it is crucial to have in-depth knowledge to appear as a well articulate individual in the industry.
