What makes data fabric great and bad for your business?

data fabricIn today’s day and age of technology, almost every industry is on the brink of a virtual transformation of its services. One of the byproducts of this trend is the rapidly proliferating sources of data. In fact, estimates suggest that the rate of generation of data in the next five years will be more than what it has been ever since its conception. So, a comprehensive data management system is currently the need of the hour. Fortunately, this is where a data fabric comes into the picture. But, what exactly is a data fabric and how can it help your business?

What is a data fabric?

Formal sources define data fabric as a “new design concept that serves as an integrated layer of data and connecting processes and is geared towards delivering the right data to the right person at the right time.” In simplified terms, it’s an ingenious approach to data management that help organizations make better use of the data that’s on offer. In addition, a data fabric aims to automate the process of data procurement and data analysis for optimizing the process of decision making.

To make it easy to grasp the underlying concept of a data fabric, it’s likened to an imaginary fabric that stretches across space and with seemingly unending borders. Its purpose is to join disparate sources of information like private and public clouds, among others. Similar to a piece of fabric, it has no real fixed shape and is amenable to be deformed by the situation, if it demands it. More importantly, the power to open it for its contents isn’t just limited to certain individuals within the firm, it extends to all those who’re employed.

What are the existing hurdles with the current systems of data management?

A data fabric intends to address some of the issues inherent to some of the data management portals that are currently in use. Some of these problems that a well-designed data architecture from the right data fabric vendors tends to smooth over include:

A)    Reliance on data siloes

Traditional systems of data management are built around a central data repository. Stakeholders have to go back and forth when it comes to accessing data which hampers the process of decision-making. Moreover, data is available in a variety of formats that need a preliminary check-up before it can go through the steps of analysis and come to a reasonable conclusion.

B)    Lack of reliability

Another issue that plagues the conventional forms of data management is the utter lack of reliability. When large data sets are being analyzed manually, there are always chances of a miscalculation. This seemingly small error can get magnified when the same erroneous dataset is used to come to a reasonable conclusion about the business. Data security is a concern too as the threat of a potential data breach looms large over companies today.

C)    Poor scalability

When a company wants to climb upwards in terms of capabilities, a major overhaul is required when it comes to older designs of data architecture. A company will need to focus on improving the existing tech infrastructure while also addressing the lack of human resources.

How does a data fabric address these issues?

A data fabric is built to connect everything within the business ecosystem under a single platform so that data is available for access at the time it is needed most. It eliminates the middle man who would otherwise be needed to make the data accessible. Moreover, data scientists need not concern themselves with mundane tasks like making a frequency chart or plotting down values in a graph.

Perceived to be the culmination of existing data technologies like data cataloging, data governance, data preparation, and data orchestration, a data fabric has the ability to function optimally in differing environments like cloud or hybrid. Since human error is minimized and the incidence of bias is reduced to nil, companies are in a better position to make data-backed decisions.

Since a data fabric allows for easy integration with newer tools like machine learning and artificial intelligence, it’s becoming the first choice for companies that are looking to shake things up and scale rapidly. The fabrics are only getting smarter with every passing day and modern corporations will be eager to reap the benefits.

What are some of the pitfalls of a data fabric?

The drawbacks of a data fabric can be traced back to its very foundation. There are a lot of moving parts to a data fabric and the complexity of its implementation can seem daunting. As the years pass by, the rate of data generation will only continue to grow and repository units will need to be constantly upgraded to accommodate such developments. Even if that goes smoothly, handling a hundred different threads, all at once and transforming them into meaningful takeaways for the business is a big ask. But, a well-designed data architecture could help in tackling some of these issues.


A data fabric is one of the latest innovations in the field of data sciences. It’s a fully integrated system that collates data from a variety of sources and helps in drawing relevant conclusions from them. It’s touted to be a one-stop solution for a growing company’s data management needs. But, the complexities associated with its implementation combined with the difficulties associated with handling the alarming rate of data generation seem to be deterrent to companies that are looking to make the shift to a data fabric.

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Hassan Abbas

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