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Data fabrics weave new advantage for insights

data fabric abstract representation
(Image credit: getty)

The central notion of data fabrics has arisen due to the distributed nature of modern data architectures and the increased pressure for data-driven insights. 

With more user endpoints, more machine-to-machine interfaces and more analytics functions driving our insatiable need for faster business intelligence and more valuable insights, we are now working with data sources located on-premises and also across hybrid multi-cloud and poly-cloud environments.

Add that assortment of environments to the fact that some workloads will require historical data at rest, some will require real-time streamed data and some will require a combination… and you can see why “weaving” a data fabric — commonly defined by leading analyst groups as a technology-enabled framework supporting many potential outputs, including data that supports insights workflows — is a non-trivial process.

A data fabric framework enables us to work across all data environments at all speeds in all data application scenarios.

Thought to be on a trajectory to experience a Compound Annual Growth Rate (GACR) of around 10% from now through to 2028, data fabric approaches will now support a wide range of analytic, operational, transactional and governance use cases for a diverse set of application use cases across all industry verticals.

A major analyst firm notes that data fabrics are a means of encouraging augmented data management and cross-platform orchestration. There is a core automation intelligence element here that can reduce the amount of human input needed to achieve the most advanced and progressive levels of data management and maintenance.

A framework to help drive innovation: data fabric vs data mesh

The difference between a data mesh and data fabric is important enough to have been defined by industry analysts. In their view, a data mesh is a solution architecture that enables building business-focused data products without specifying the technology needed, and a data fabric is a framework—an implementation design flexible enough to support multiple outputs and uses.

What we will all achieve by adopting data fabric frameworks is a chance to more comprehensively manage the very dispersed nature of modern data, for the highest value to the business.

cloud computing city concept

Data fabric frameworks can glean business insights from complex information in the modern age of cloud and hybrid data architectures (Image credit: Getty)

Given the amount of verification, deduplication, ratification, augmentation and data retirement defenestration (for stale data) that we will need to be able to execute inside modern data estates, the data fabric represents a crucial “blanket” data management framework (no pun intended, unless you insist) by which we can avoid the vicious cycle and unwelcome effects that come from poorly-managed data.

We can pinpoint four cornerstone advantages enterprises can achieve by adopting data fabric frameworks; these are a set of benefits which will manifest themselves at varying degrees inside different organisations, but will all typically be present as a set of conjoined data-driven advantages. Essentially, these cornerstones gravitate around insights, innovation, information governance and insured trustworthiness.

These were some of the challenges that Koch Industries faced, as an “enterprise of enterprises” with many business units undergoing digital transformation. They sought a flexible data fabric to improve data quality, governance, and ultimately to unlock the business value of their data.

By using a data fabric platform, the Koch team was able to design autonomous data spaces for each of its dozen businesses, enable a shared data platform, and make progress towards streamlining data sharing across the enterprise. Since piloting their new data fabric, Koch has built 10 tenants with eight in production. So far, each new tenant experiences faster time-to-value than the one before.

According to Jason Wingate, Solutions Architect at Koch Global Services, "Our data governance platform needed to solve problems with out-of-box functionality and be fully customisable if our IT teams wanted to pursue that.” Through the new data fabric, the team reduced the development cycle, ramped up efficiency, reduced costs, and improved data quality, reporting, and functions. Their robust data fabric has positioned Koch not only for better information governance, but for more insights, innovation, and future success.


The value of a data fabric goes beyond governance and can fuel high-impact insights. In a world where data is now the lifeblood of all businesses, organisations need to think about their data management competency in the same way that they think about their installed base of operational equipment, the quality and standard of their procured services and the level of their staff skills base.

As enterprises, large and small, adopt data fabrics to automate and accelerate data management, they can take advantage of Artificial Intelligence (AI) and Machine Learning (ML) in data management workflows to augment their approach to data and ultimately gain deeper business insights from it. 

While insights use cases often are specific to a given industry — for example, answering the question of “what equipment might be in need of maintenance now to avoid failure?” for manufacturers — any industry with complex data estates will benefit from a data fabric approach.


digital transformation concept

A data fabric approach will make it easier for businesses to transform their business through data-driven insights (Image credit: Getty)

Secondly, let's consider disruptive innovation fuelled by data. Developing and utilising a robust data fabric framework enables organisations to put the entirety of their total data estate to work. This breadth and scope acts as a crucial prime mover advantage when seeking data-driven advantage, such as bringing disruptive new products and services to market.

A business that leverages a data fabric approach will find it easier to transform their business through data-driven insights that yield a new level of resilience through innovation. Such an organisation will be also poised to surpass its competitors with AI-infused acceleration and agility.

Information governance

Our third cornerstone here stems from a data fabric framework’s ability to leverage and support compliance and governance.

The global marketplace is characterised by an increasingly complex array of regulatory and compliance needs. This means that enterprises need data management to function from a base of controlled access, auditability and traceability. These controls must apply across users, processes and data itself. 

With new regulatory stances being applied by the EU, USA and the rest of the world on a year-on-year basis, this is a core requirement for any business that seeks to succeed.

The unified view provided through data fabric frameworks can simplify and streamline this complexity.


A data fabric framework provides a form of “insurance,” or  ensured trustworthiness in data and its capabilities. The very definition of a data fabric involves taking a unified approach to data management. This instantiates that only curated, trusted data is accessible for use.

As we see in the Koch Industries story, in adopting a data fabric framework, transparency across the insights workflow is enhanced. Information diversity continues to spiral and data workloads are becoming more convoluted, more interconnected and more concurrently complex in their nature. Understanding what a data fabric framework can do to manage these challenges and weave business value from information complexity is a necessity in the modern age of cloud, hybrid data architectures, and the explosion of data volumes and velocities. 

Today, the way leading enterprises use data is cut from a different cloth — one increasingly woven with data fabric frameworks.

Lori Witzel is Director of Research for Analytics and Data Management at TIBCO.

Lori Witzel
Lori Witzel

Lori Witzel is Director of Research for Analytics and Data Management at TIBCO. As part of the TIBCO's global Thought Leadership Team, Lori develops and communicates next-generation analytics and data management research and perspectives. Lori provides guidance that helps CEOs, CMOs, COOs, and other non-technical leadership to innovate, collaborate and grow their businesses through the power of Digital Transformation. In addition to generating and sharing insights in collaboration with TIBCO customers, partners, industry analysts, and employees, Lori also researches and writes white papers, articles, and blogs and is a regular speaker at industry events.