SAP Business Data Cloud is not just a new platform for data and analytics. It is also an important part of SAP’s future roadmap.
In this episode of Implema Talks, Johan Berg from Implema talks with Anders Heimer from SAP about why SAP BDC is becoming relevant for SAP customers moving forward, how the platform connects data and AI, and why companies need to see their data strategy and AI strategy as a unified whole.
SAP Business Data Cloud (SAP BDC) will be a central part of SAP’s future roadmap because companies need a more cohesive data platform to use AI in a business-oriented and reliable way.
According to Anders Heimer from SAP, the SAP BDC Roadmap is about helping customers build a unified data platform where data can be used across silos, with context, metadata, and business understanding. For SAP customers, this means BDC should be seen as a strategic part of the future data and AI architecture, not just as a new technical initiative.
In the conversation, Anders Heimer describes SAP BDC as a platform rather than a single product. SAP has expanded its technology platform towards data lakehouse, data fabric, and data mesh architecture.
This means BDC will help customers create a more unified data foundation. Not just for reporting and analytics, but also for AI, automation, and future digital ways of working.
For many companies, this is a concrete challenge. Data is often found in silos. It resides in different systems, processes, and business areas. When the organization wants to use AI, having access to data isn’t enough. The data must also be understood in its context. This is where SAP BDC becomes strategically important.
An important point is that AI doesn’t function optimally if it only has access to raw data. For AI to create business value, it also needs to understand the context surrounding the data.
For example, this could involve what an order means, what type of order it is, how it relates to the customer relationship, which processes it affects, and what dependencies exist between different business objects.
In other words: AI doesn’t just need data. AI needs business context.
SAP BDC addresses this by combining data, metadata, semantics, and relationships between different data products and business objects.
“AI can’t just run on data. It also needs to understand the context around the data” – Anders Heimer, SAP
This is one of the most important insights in the episode. For companies that want to use AI in their business processes, the data foundation becomes crucial. If data is isolated in silos, it becomes difficult to ask broader questions, create reliable AI answers, or automate decisions across process boundaries. Therefore, companies need a more cohesive strategy for both data and AI.
According to Anders Heimer, a key part of SAP BDC’s strength lies in its ability to add business context to data.
SAP data is often closely linked to a company’s most central processes: orders, purchasing, finance, production, inventory, deliveries, and customer relationships. This puts SAP in a unique position when companies want to use data and AI connected to business processes.
In SAP BDC, data products, metadata, and semantics become vital components. Data products can help customers get standardized content from applications in lake format, with metadata surrounding the data. The next step is understanding how different data products are interconnected.
This is where SAP’s so-called knowledge graph becomes relevant. It helps describe the relationships between data, processes, and business objects.
In the episode, Anders highlights that companies wanting to use AI more broadly need trusted data.
Trusted data isn’t just about data quality in a technical sense. It’s also about data being understandable, governed, and linked to the right business context.
For an SAP customer, this can mean that:
It is only when data is reliable and business-aligned that AI can become truly relevant.
“Customers need to align their data strategy with their AI strategy.” – Anders Heimer, SAP
This is an important conclusion. Many organizations today talk about AI strategy but still treat data as a separate issue. In practice, they are linked. An AI strategy without a clear data strategy risks becoming theoretical. A data strategy without a link to AI and business value risks becoming an internal technical project. SAP BDC makes that connection clearer.
According to Anders Heimer, the response from SAP customers has been very positive. Customers start from different angles depending on their needs. Some focus on traditional data warehousing and analytics. Others start by sharing SAP data to, for example, Databricks.
The important thing is that SAP BDC doesn’t require all customers to start the same way. The platform can be used step-by-step and based on different priorities.
For some, the first step is about better reporting. For others, it’s about data sharing, AI readiness, or creating a more long-term platform for enterprise data.
For companies already using SAP that want to understand what role BDC can play moving forward, the first step isn’t to start a massive transformation program. A better start is to map the current situation and identify where the business value is greatest.
Relevant questions to start with:
Once these questions are clear, it becomes easier to choose the right starting point. Feel free to use our SAP BDC Workshop to get started.
SAP Business Data Cloud is becoming an important part of SAP’s future roadmap because it addresses one of the biggest challenges in many organizations: creating a reliable, cohesive, and business-aligned data foundation for AI and analytics.
For SAP customers, it’s not just about collecting data. It’s about understanding data in the right context.
That’s where SAP BDC becomes strategically interesting. The platform connects data, metadata, semantics, data products, and business processes in a way that can help companies build a stronger foundation for both analytics and AI.
The most important question for SAP customers therefore becomes not just:
What is SAP Business Data Cloud?
But rather:
How can SAP BDC help us build a common data and AI strategy?
SAP Business Data Cloud is SAP’s platform for data, analytics, and AI. It helps companies create a more cohesive and reliable data foundation across different systems and processes.
SAP BDC is important because SAP uses the platform as a future reference architecture for data, analytics, and AI. For SAP customers, it therefore becomes relevant to understand as part of their long-term IT and data strategy.
A unified data platform is a consolidated data platform that makes it possible to use data across different systems, silos, and business areas. The purpose is to create a more consistent foundation for analysis, AI, and decision support.
AI needs to understand what data means in relation to business processes, objects, and concepts. Without context, AI risks providing answers based on data but lacking business understanding.
Trusted data is data that is reliable, understandable, governed, and linked to the right business context. It is a vital prerequisite for using AI and analytics in business-critical processes.
SAP customers should start by mapping their current data landscape, identifying key silos, and linking data needs to concrete AI and analytics cases. After that, a step-by-step roadmap can be developed.
Business Development Manager SAP
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