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Author's profile photo Savannah Voll

What is a Business Data Fabric?


For decades, companies have spent billions of dollars on new data architectures to drive better decision-making. Unfortunately, these projects often involve extracting and replicating data, which results in displacing the valuable business context.

Companies lose the elements of data that provide value and meaning, including the metadata, logic, and security. They’re required to spend additional time and money to rebuild the business context of the data, and in many cases, they’re unable to.  

In the endless pursuit of new technology there’s been a fundamental error: focusing on the technology rather than on the data, which is where the value is. We need to shift the focus back to the data.  

Cloud Transformation  

Cloud technology has advanced to become faster, less expensive, and easier to scale, but it’s also compounded the issue. New data sets spawn new projects while on-premise sources remain, meaning both the volume and complexity of the data has increased.  

We’ve spoken to many organizations about their data challenges and a few universal needs have emerged. Business users are looking for self-service access to trusted data in real-time to make better, more timely decisions, and IT users want to centralize governance and simplify the ever-growing data landscape.  

In many ways, these are opposing forces and there’s often tension between the groups – centralized governance vs. decentralized access. 

Business Data Fabric 

The best approach isn’t to move data around and then reconstruct all the context that’s been lost. It’s to have a business data fabric – a data management architecture that focuses on delivering an integrated, semantically-rich data layer over underlying data landscapes to provide seamless and scalable access to data without duplication. A business data fabric differs from a standard data fabric in that it keeps the business context and logic intact.  

This architecture provides a number of benefits:  

  • Self-service access to trusted data breeds agility and accelerated, accurate decisions 
  • Comprehensive data governance assures every stakeholder that private data stays private 
  • Real-time data, infused throughout the data architecture helps business users, partners, and employees make in-the-moment improvements 
  • A simplified data landscape reduces costs and technical debt while maximizing current investments 

SAP Datasphere, a comprehensive data service built on the SAP Business Technology Platform (SAP BTP), is the foundation for a business data fabric. It enables organizations to deliver meaningful data to every data consumer — with business context and logic intact. It provides capabilities from data ingestion through self-service data access across SAP and non-SAP data. 

Real-World Application  

Messer Americas leveraged SAP Datasphere in the development of their business data fabric. They compete in the dynamic industrial gases sector, which means they must respond quickly to changing market conditions. However, siloed data and inconsistent analytics modeling approaches slowed their decision-making. Now, they’ve built a trusted and consistent view of the data to support business-critical decisions across the enterprise. 

“The business data fabric architecture enables us to bring SAP and non-SAP data together in the seamless and self-service way we’ve been envisioning,” said David Johnston, Chief Information Officer at Messer. “SAP Datasphere provided us with a solution to build a harmonized layer, or business data fabric, across SAP and non-SAP, cloud or on-premise data sources, making the best use of our existing investments in SAP, Microsoft Azure, Salesforce, and Oracle.”  

By adopting this approach, Messer consolidated their 12 data sources into a single solution, and now, 100% of their data modeling tasks are achievable using self-service tools. 

Learn more  

To learn more about the business data fabric, read the new e-book. This resource provides a deeper dive into the topic, including:  

  • The difference between data fabric, data mesh, and business data fabric 
  • The architectural components of a business data fabric  
  • The value and benefits of a business data fabric  

Get started with the What is a Business Data Fabric? e-book today.  




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      Author's profile photo Martin Kreitlein
      Martin Kreitlein

      Hello Savannah,

      please don't take it personally, but what you describe here is eventually nothing more than a justification for a story to sell SAP Datasphere ... and you should add this 🙁

      If you go back in time - and I don't know if you really have experience about what I'm telling you - you will recognize that during the last 20 years, SAP did not provide any better option ... so you cannot say, we did "everything wrong" in the past.

      In the 2000s the ERP system and not even the BW system have been able to handle real big reporting volumes in flat tables ... that is why Infocubes were introduced, with capabilities of aggregates.

      Then, the BI-Accelerator supported reporting performance even more.... until finally SAP HANA became a potential database under the BI reporting component.

      All in all, there was the need to work with different systems, for their optimized purpose.

      Even today, SAP's strategy proves that e.g. since planning from SAC directly into S4 tables is not a valid scenario.

      What I want to say is that your description of a "bright new world" is still limited even by one more separate system... and in the end we're just doing the same, we did for the last 20 years.

      BR, Martin

      Author's profile photo Dietmar Splitt
      Dietmar Splitt


      There is no context IN the data, so you can't lose it when you transfer data between systems.

      Datasphere or Fabric don't give you the magic business-context, they are just new/additional systems for combining SAP and non-SAP data.

      So you and your IT department still have to prepare a lot of data to give it a business meaning before it can be used with "self-service" 😉