IBM ranks second highest in the Data Fabric Use Case

See why in the 2021 Gartner Critical Capabilities for Data Integration Tools.

What is a data fabric?

A data fabric is a data management architecture that can optimize access to distributed data and intelligently curate and orchestrate it for self-service delivery to data consumers. With a data fabric, you can elevate the value of your enterprise data by providing users access to the right data just in time, regardless of where it is stored. A data fabric architecture is agnostic to data environments, data processes, data use and geography, while integrating core data management capabilities. It automates data discovery, governance and consumption, delivering business-ready data for analytics and AI.

Why do you need a data fabric?
Top performing enterprises are data driven. However, several challenges block them from fully exploiting all data. Lack of data access. Numerous data sources and data types. Data integration complexities. Research shows that up to 74% of data is not analyzed in most organizations¹ and up to 82% of enterprises are inhibited by data silos².

With a data fabric, your business users and data scientists can access trusted data faster for their applications, analytics, AI and machine learning models, and business process automation, helping to improve decision making and drive digital transformation. Technical teams can use a data fabric to radically simplify data management and governance in complex hybrid and multicloud data landscapes while significantly reducing costs and risk.

Data fabric use cases

Self-service data use

Person working with a laptop in an office

Enable self-service data consumption

Self-service, real-time data access lets business users spend less time on finding the right data and more time uncovering tangible insights that drive faster response to market changes.

Automated governance

Person working with 2 laptops and a large monitor

Automate governance and data security

Apply industry-specific governance rules quickly across enterprise data by using active metadata to enable automatic policy enforcement for data protection.

Multicloud data integration

Overhead view of large traffic circle

Integrate data across any cloud

Make trusted data available quickly in hybrid and multicloud data landscapes. Automate data engineering to simplify access to data. Re-use data management capabilities for greater efficiencies.

Data fabric features

Democratize quality data

Augmented knowledge

An abstraction layer that provides a common business understanding of the data and automation to act on insights

Intelligent integration

A range of integration styles to extract, ingest, stream, virtualize and transform data, driven by data policies to maximize performance while minimizing storage and egress costs


A marketplace that supports self-service consumption, enabling users to find, collaborate and access high-quality data

Unified data lifecycle

End-to-end lifecycle management for composing, building, testing and deploying the various capabilities of a data fabric

Multimodal governance

Unified definition and enforcement of data policies, data governance and data stewardship for a business-ready data pipeline

Designed for AI and hybrid cloud

An AI-infused composable architecture built for hybrid cloud environments

Why the IBM data fabric

Holistic view across a distributed data landscape

Intelligently integrate and unify data across hybrid and multicloud to deliver trusted data and speed time to business value.

Automated governance

Automate the activation and enforcement of policies and rules across all data consistently. Increase visibility and collaboration on any cloud while reducing compliance risks.

Faster, more accurate insights

Consolidate data management tools and minimize data duplication for faster access to higher quality, more complete data that renders deeper insights.

The platform

More on data fabrics

Data fabric versus data lake versus data warehouse

Data management tools have evolved from databases to data warehouses to data lakes, each being developed to help solve new business problems. A data fabric is the next step in the evolution of these tools. It lets you continue to use the disparate data storage repositories you’ve invested in while simplifying how you manage the data residing in them. A data fabric helps you optimize your data’s potential by automating data integration, embedding governance and facilitating self-service data consumption. This fosters data sharing and helps accelerate data analytics for faster insights.

Data fabric versus data virtualization

Data virtualization is one of the technologies that enables a data fabric approach. Rather than physically moving the data from various on-premises and cloud sources using the standard ETL (extract, transform, load) process, the data virtualization tool connects to the different sources, integrates only the metadata required and creates a virtual data layer. This allows users to leverage the source data in real time.

In the current knowledge era, the volume of data has increased tremendously, but the amount of information extracted from the data is not keeping pace. Because it is often too difficult to access much of the data, organizations are leaving it — and the potential insights it holds — unused, resulting in a knowledge gap.

A data fabric architecture with data virtualization capabilities helps reduce this knowledge gap. Organizations can access data at the source without moving it, helping to accelerate time to value through faster, more accurate queries.

Try the IBM data fabric

Contact us now to schedule your 7-day, no-cost assisted trial.

¹ Rethink Data: Put More of Your Business Data to Work – From Edge to Cloud (link resides outside IBM) (PDF, 8.3 MB), Seagate Technology, July 2020

² “Are Data Silos Killing Your Business?” (link resides outside IBM) Michael Goldberg, Dun & Bradstreet, May 2018