5 Steps to a Business Data Fabric

Managing and leveraging data can be a daunting task. Businesses grapple with complex datasets from many different and unconnected sources, including operations, finance, marketing, customer success, and more. Plus, a lot of organizations are geographically dispersed and have complicated use cases or specific needs, like storing data across cloud, hybrid, multi-cloud, and on-premises devices. 

A business data fabric offers a solution. 

This data management architecture provides an integrated, semantically-rich data layer over underlying data landscapes to deliver scalable access to data without duplication. In other data platforms, when data is extracted from core systems, much of its original context is lost. A business data fabric preserves this context, helping ensure the data remains meaningful and relevant for decision-making, regardless of its origin.  

This approach offers a number of benefits including enhanced data accessibility, improved data governance, and accelerated insights. 

But how do you get started? 

Implementation framework 

Let’s look at a high-level framework for implementing a business data fabric architecture in your organization.  

1. Data Ingestion 

The first step is to ensure that all your data, whether it’s structured or unstructured, can be easily ingested into the system. A business data fabric, with its open data ecosystem, allows for simple data ingestion, regardless of the source or the format of the data. 

2. Data Integration 

Data from various sources must be integrated and transformed into a unified format easily consumed by data users. The interoperability of a business data fabric enables data from different sources to be combined and connected rather than being moved around. 

3. Data Governance 

With the growing complexity and volume of data, governance becomes an increasingly important topic. This includes ensuring data quality, privacy, and compliance with various regulations. A business data fabric ensures effective governance by maintaining metadata, lineage, and control measures. 

4. Data Cataloging 

This involves creating an inventory of data assets and their metadata. The catalog serves as a single source of truth for users to find, understand, and trust the data they need. It’s a critical component of the business data fabric that allows data consumers to understand the business semantics. 

5. Data Consumption 

This is about delivering the right data, in the right format, at the right time, to the right people. The business data fabric supports data federation, which enables unified and consistent access to data across diverse sources, reducing redundancy. It ensures data is presented in business-friendly terms and contexts, making it simple for data consumers to interpret and use the data for their specific use cases. 

This is where SAP provides the foundation for a business data fabric: SAP Datasphere. 

Transform your organization with SAP Datasphere  

SAP Datasphere is a comprehensive data service that empowers users to provide seamless and scalable access to mission-critical business data.  

It makes it easy for organizations to deliver meaningful data to every data consumer with business context and logic intact. As organizations need accurate data that is quickly available and described with business-friendly terms, this approach enables data professionals to permeate the clarity that business semantics provide throughout every use case. 

In a major moment for our industry and customers, SAP is partnering with other open data partners — Databricks, Collibra, Confluent, DataRobot, and Google Cloud — to radically simplify customers’ data landscapes. By closely integrating their data and AI platforms with SAP Datasphere, organizations can access their mission-critical business data across any cloud infrastructure. 

SAP Datasphere, and its open data ecosystem, is the technology foundation that enables a business data fabric.  

Learn more   

Read the new e-book to learn more about the practical applications of a business data fabric, including:  

• Why you need a business data fabric 
• How to implement a business data fabric  
• Five business data fabric use cases 

Get started with the Five Steps to a Business Data Fabric Architecture e-book today.