The challenge comes from two angles simultaneously. On one hand, data is becoming increasingly critical to organizations. On the other hand, enterprise IT overviews are becoming more distributed, diverse and complex. Data modernization and integration is essential to compete and win in this new highly digitized scenario.

The architecture known as data fabric provides management capabilities that enable single visibility into the entire data set regardless of whether it is located in the cloud, on premise or at the edge of the network. In addition to being agnostic to geography, it is also agnostic to environments, processes and utility. The idea of “fabric” speaks of an ability to connect storage spaces, types and sources of data with the appropriate methods to access them in an accurate and timely manner.

The innovation consultancy, Gartner, selected it as one of the top 12 technology concepts for 2022 and predicts that by 2024, 25% of data management vendors will provide a complete framework for data fabric, compared with the current 5%.

From layer to fabric

Gartner itself defines this framework as a concept that includes an integrated, reusable layer of data, which it calls a fabric, linked by connecting processes that enable that data to be created and used in all environments. Data fabric continuously identifies and connects data from different applications to discover unique, business-relevant relationships. Specifically, it automates the discovery, governance and consumption of data, enabling enterprises to extract the maximum value from it.

Among other things, with this new paradigm it is possible to establish protection and security strategies (including backup and restore or disaster recovery) or define access and control based on unique policies that impact the total data set.

As companies move to multi-cloud environments, the adoption of the data fabric concept becomes more imperative.

Farewell to silos

One of the major problems facing companies that want to move towards a data-driven model, is the existence of silos: disconnected infrastructures that are in some cases even incompatible with each other.

Data fabric breaks with that logic: an integrated end-to-end environment ensures data consistency and quality, improves the results of AI-driven analytical tools and consequently leads to better decision making. It also enables a real-time 360° view of any element linked to the business: a customer, an item, a supplier or an asset just to name a few.

Additionally, from the point of view of IT administrators, it enables greater control over the costs associated with data handling and easier configuration and management.

Human-machine collaboration

Gartner warns that this is not simply a combination of technologies but a different approach that involves new forms of human-machine collaboration, among other things.

Thanks to machine learning and automation, the more data fabric is used, the better it gets. First, it monitors data pipelines performed by human operators as if it were a passive observer. Then, once trained, it begins to suggest much more productive alternatives.

In a few words, a strategy supported by such a unified platform helps solve the big problems: who uses the data, how, and for what purpose. Where? It’s no longer important. The ultimate goal? That the right person has what they need, at the right time and through the most appropriate method so that they can bring maximum value to the organization.