Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. In this edition, we’ll learn about a framework called data fabric that can help solve a plethora of data management requirements in an organization.

Credits: ManageEngine Design Team

It’s no secret that data is the new gold, and organizations have been taking steps to get the most out of it. Immense effort is being taken to integrate traditional silo-based data systems and the current dynamic structure as well. Not just from internal sources, but data from external sources is also being carefully intertwined within systems to get enhanced outcomes.

With so much being done around data, it’s only fair to devise a framework that would bring all data streams together for a holistic perspective. This framework should provide continuous and systematic functionality across all endpoints and platforms, i.e. both on-premises and cloud, to allow seamless data access and dynamic data approaches, and to make data management a whole lot easier. For this, consider the data fabric framework—a set of architectures and services that can not only improve scalability and reusability of model data, but reduce design and operational difficulties.

A data fabric framework helps discover, access, and manage data while maintaining data quality. It has the capability to blend and work well with other advances in technology, like AI and ML. For instance, based on past purchase data patterns, AL and ML can suggest suitable data-based outcomes to reduce customer churn rate and improve retention rate.

As real-time data sharing is of utmost importance, data fabric uses a network-based architecture to handle data flow. This way, it can help integrate layers of data and applications, and highlight relevant insights. Further, business analysis is easier with this framework in place, which will allow leaders to focus on business and digital transformation instead.

Here’s a list of some interesting finds that detail what data fabric is and how it can be implemented in an organization:

  1. What Is Data Fabric?

Due to the key capabilities that data fabric supports, plenty of high-scale and high-speed use cases can be handled within an organization’s architecture. Some of these include getting a 360-degree view of customers and adhering to compliance requirements like the GDPR.

  1. Data fabric offering a robust solution to data management challenges

By using a metadata-driven architecture available due to a data fabric network, system optimization is ensured. AI can also perform a dynamic integration between data and processes to seamlessly enable the right data to reach the right destination through the shortest possible route.

  1. 5 Steps to Implementing a Modern Data Fabric Framework

For a successful data management strategy, it is important to create a data fabric framework. This interlinks concepts, relationships, and entities and provides enriched insights suitable for an enterprise’s digital transformation requirements.

  1. Seven strategic pillars of a leading business data fabric

Getting business-relevant data through a single pane of glass is a struggle that every organization faces. To eliminate this difficulty, different sources of data must be stitched together to get a consolidated view. Data fabric not only enables this, but also ensures democratization and governance.

  1. The Dawn of Data Fabric Marketplace! How to Make it Happen?

Since the opportunities are immense, data providers and consumers can use data as a commodity to emulate a marketplace. It would also enable self-service, where data exploration, monitoring, and governance can mature further.

One of the major challenges that must be addressed while implementing a data fabric framework is security. Since data moves from one point to another, it should be made mandatory to encrypt data while at rest and in transit. In addition, having a Zero Trust policy in place will help protect against cyberattacks.

Another challenge is keeping up with regulations like the GDPR. But since data fabric in itself establishes traceability, finding the location of data should be easy. Due to rising business needs, it’s only a matter of time until organizations begin implementing a data fabric framework to deal with major data management challenges. Let’s wait and see how they catch up to this inevitable trend.