From scattered data to commercial impact: Salesforce Data Cloud
Your organization probably has plenty of data, but does it sit where you actually need it? At many organizations, customer information is trapped in silos: order history in the ERP, click behavior on the website, tickets in a legacy service system, and contracts in yet another database.
The result: nobody has a complete picture. Marketing sends emails to customers who just filed a complaint, and Sales misses visibility into recent purchases. That changes the moment these sources are connected in real time: what emerges is one harmonized customer profile that’s immediately usable across every department.
The unavoidable question: why do I need Data Cloud?
This is the question we get most often: “Isn’t my data already in Salesforce or my Data Warehouse? Why do I need an extra layer?”
The answer is simple: speed, scale, and context for AI.
Traditional CRM systems are built for transactions (an order, a touchpoint). They’re not built to process millions of real-time data points, like IoT signals or website visits. A Data Warehouse is good for storage, but often can’t activate that data directly in a sales conversation.
Data Cloud does three things your current system can’t, and that are essential for the future:
- Harmonization for AI: If you apply AI, like Agentforce, to polluted data, you get unreliable answers. Data Cloud is the filter that gives AI a single source of truth. Without Data Cloud, Agentforce doesn’t work effectively.
- Streaming data: It processes live data. So not “the customer looked last week,” but “the customer is looking right now.”
- The foundation for everything: Whether you’re rolling out advanced marketing automation, Tableau analytics, or autonomous AI agents, Data Cloud is the infrastructure that makes it possible.
Data strategy for complex landscapes
Implementing Data Cloud is a strategic choice, not a simple flip of a switch. In the manufacturing industry, we see complex IT landscapes with heavy-duty ERP systems and large data volumes. We know how to model those complex flows.
The end of silos
Connect data from SAP, Microsoft, AWS, Google, or Snowflake directly to your CRM (Zero Copy: reading data straight from the source) without physically moving any data.
Real-time relevance
Respond to what a customer is doing right now, not to historical reports.
Future-proof
We design the architecture so you’re ready for the next step in digitalization.
What does this deliver in practice?
Data Cloud turns raw data into action.
One 'Golden Record'
No more duplicate records or polluted lists. Data Cloud recognizes that ‘J. Jansen’ in your webshop is the same person as ‘Jan Jansen’ in your ERP, and merges these profiles into one ‘Unified Individual’. This is the only profile your Sales and Service teams need to see.
Smarter segmentation
Marketing can suddenly segment on data that was previously out of reach. Think of a campaign targeted at customers who’ve “been a customer for more than 3 years” (ERP data), “viewed the price list in the past week” (web data), and “have no open tickets” (service data).
Automation triggered by external events
Say a machine sends an IoT signal indicating a part is nearly worn out. Data Cloud picks up this signal and immediately creates a task for the account manager or kicks off a service process.
Jaäl Pekelder
Sales Consultant
Use case to technology
We don’t connect data just for the sake of connecting it. We focus on value.
Use case definition
We identify the problem we’re solving. (For example: predicting churn, spotting upsell opportunities, or reducing service costs).
Data mapping
Where does the required data live, and what’s its quality?
Harmonization
We connect the sources and make sure the fields line up logically.
Is your data ready for AI?
Get in touch?
Data is the foundation. Without a solid foundation, your AI strategy collapses. Let’s look at how we can turn your data flows into a workable model for the future.
Frequently Asked Questions
What is the difference between Data Cloud and a Data Warehouse?
A Data Warehouse (like Snowflake or BigQuery) is designed for storage and after-the-fact historical analysis. Data Cloud is designed for action. It sits as a layer on top of your warehouse and makes that data immediately usable (‘activation’). While a warehouse tells you what happened last week, Data Cloud uses that data to fire a trigger right now in Salesforce Flow, Marketing Cloud, or Agentforce.
Do I need Data Cloud if I already use Salesforce?
Standard Salesforce (CRM) is built for transactions (an order, a touchpoint). It’s not designed to process millions of signals, like click behavior on your webshop or IoT data from machines. Data Cloud can handle these large volumes, harmonizes them, and displays them directly on the customer profile in the Salesforce UI. That gives your account manager the complete picture without having to check five different systems. Data Cloud also includes a built-in ‘vector database’. This means you can also search unstructured data, like PDF contracts or emails, intelligently and based on context (similarity search). This is an absolute requirement for getting AI to generate the right answers within your CRM.
What is a Unified Customer Profile?
We also call this the ‘Golden Record’. In your systems, a customer often exists twice: as ‘J. Jansen’ in the webshop and ‘Jan Jansen’ in the ERP. Data Cloud recognizes this is the same person and merges the profiles into one. As a result, Marketing, Sales, and Service all look at exactly the same information, instead of fragmented pieces.
How does Zero Copy integration work?
Previously, you had to physically copy data from system A to system B (ETL), which is slow and error-prone. With Zero Copy, Data Cloud ‘looks’ directly into your external data lake (like Snowflake, Google BigQuery, or Databricks) without moving the data. The data stays at the source, but is immediately available in Salesforce for segmentation and AI.
Is Data Cloud required for Agentforce?
Simple tasks don’t need it. Intelligent autonomy does. Agentforce is only as smart as the data you feed it. Without Data Cloud, the agent only sees what’s in Salesforce. With Data Cloud, the agent also has context from your ERP, your webshop, and your legacy systems. This prevents the AI from making decisions without understanding the full context, and ensures the agent acts on the complete, up-to-date customer picture.
How do you get started with Data Cloud without migrating everything at once?
We work ‘use case driven’: one business problem at a time. We connect only the data sources needed for it, harmonize them, and deliver value. Only then do we move on to the next use case. This keeps the project manageable.
How does the pricing model work?
Data Cloud runs on a consumption model (credits). You pay for what you process and store. Because we work from specific use cases, we can accurately estimate upfront how much data you’ll need and what impact that has on your credits. This avoids surprises down the line, and you don’t pay for data you end up not activating.