What is Data Fabric? Definition & Architecture

What is Data Fabric? Definition & Architecture

With the increased importance of data to businesses, it’s no surprise that there are more and more ways to organize and store data.

From local network storage, to the cloud, to data lakes, you’re spoiled for choice!

But as companies strive to be more competitive, efficient, and profitable, these growing and disparate data sources can become increasingly problematic.

You’ll often end up with huge amounts of data, split across different locations, apps, and formats. Which combined with rapidly increasing regulatory pressure, can create more problems than it solves.

The solution isn’t to create yet another way to store data, but to find a way to bring all of this data together in a manageable way.

Which is exactly what Data Fabric does!

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What is Data Fabric?

Data Fabric is an architectural approach that enables organizations to break down data silos and make sure all data is governed, accessible, and secure.

It gives companies access to all of their data, across data warehouses, data lakes, relational databases, and SaaS applications. Plus anywhere else they have data stored.

This is achieved using a virtualization layer to aggregate access, then utilizing robust data integration tools to create a data catalog.

This catalog can then be used by business analysts, data scientists, app developers, and more to efficiently and securely carry out their work.

An easy way to imagine it is like WhatsApp chats. Before, you had a bunch of individual chats, and it was difficult and time consuming talking to everyone separately.

Data Fabric is a group chat that brings everyone together, and makes it easy to keep track of what’s going on, and communicate with everyone at once.

Related: How to Build a Data Catalog

Why use Data Fabric?

International Data Corporation, a global market intelligence firm, reports that 83% of CEO's want their organization to be more data-driven, and are investing in growing their Data Cultures.

But there is a huge difference between calling yourself data-driven, and actually utilizing data to grow and plan for the future.

Data Fabric provides a blueprint to help organizations leverage their data and get the most out of their data-driven initiatives. It helps organizations to create a unified data environment, where data can be accessed, manipulated, and analyzed from multiple sources in a secure and compliant manner.

It also provides the infrastructure to enable teams to develop and deploy predictive models quickly and cost-effectively.

Another huge pressure on companies is compliance with regulations like GDPR, CCPA, HIPAA, and FCRA. These specific regulations may not apply to everyone, but every company has its own regulations to adhere to, and the more data you have, the harder this becomes.

The Data Fabric architecture makes this much simpler, as you can access all your data inside the data catalog, and monitor for breaches and compliance risks.

To achieve this, it uses active metadata to automate policy enforcement, mask/redact data, and create role-based access control (RBAC).

This means organizations can meet their data governance and privacy requirements, while also allowing them to take advantage of the latest data-driven technologies.

Related: 3 Data Privacy Compliance Challenges that can be solved with OvalEdge

Data Fabric Benefits


Data Fabric provides robust security for data, with access control, data masking, and encryption. This helps organizations meet their compliance requirements and protect sensitive data.

It also helps reduce the risk of data breaches, and gives organizations more control over who has access to their data.


Data Fabric simplifies the process of data integration, making it more efficient for organizations to access data from multiple sources and build a unified data environment. With this integrated approach, organizations can quickly and easily aggregate data from different sources and get more value from their data.

This allows for a greater range of insights to be derived from the data, making it easier to make informed decisions and stay ahead of the competition. Furthermore, the single unified data environment ensures that all data is kept secure and organized, allowing for more effective data management.

Better understanding of the data

Implementing a Data Fabric architecture helps organizations better understand their data. By having access to all their data in one place, it is much easier to analyze, identify patterns, and gain insights.

It also allows organizations to compare different data sources to better understand how the data is being used, and how it is changing over time.

This makes it easier to spot problems and opportunities, and to make informed decisions based on the data.


As we’ve already touched on, Data Fabric provides the governance needed to ensure that data is handled in a compliant manner. It uses active metadata to automate policy enforcement, mask/redact data, and create role-based access control (RBAC).

This helps organizations to meet their data governance and privacy requirements, and allows them to take advantage of the latest data-driven technologies.

This also provides the infrastructure to monitor for breaches and compliance risks, making it easier to stay on top of data security.

Related: Top 5 Data Governance Use Cases


A term thrown around so much it’s often discarded as a buzzword, AI is very much here to stay, and there is one thing all AI needs…


Data Fabric makes it easy for organizations to take advantage of AI and machine learning. By providing a single source of data, it eliminates the need to search through disparate data sources, and makes it easier to find the data you need for your models.

Plus, the active metadata and security features provided by Data Fabric tools make it easier to ensure data is handled by AI in a compliant way, and reduce the risk of data breaches.

Best practices for implementing Data Fabric

Solid governance

If it’s not already clear, data governance is at the heart of Data Fabric, and you need to take it seriously to get the benefits. This includes things like:

  • Organizing all your data sources and consolidating your data into a single location.
  • Ensuring that all data adheres to data privacy regulations and internal company policies.
  • Once you have organized your data, you need to figure out how to show it to your team.
  • Use methods and technologies to ensure data is secure and well-managed
  • Ensure people can only access the data they’re permitted to access


Data Fabric also needs to enable discoverability. This means making sure that users can easily find the data they need, and that the data is up to date and accurate.

To achieve this, organizations should leverage metadata, data cataloging, and search tools to ensure users quickly find the data they need.

Use a self-service platform (like OvalEdge)

We’ve covered what Data Fabric is, why you should use it, and what the benefits are, but we need to be clear. Data Fabric is an architecture, and can’t be achieved without tools that make it possible.

This is where self-service platforms come in!

Self-service platform tools like OvalEdge help organizations to quickly and easily implement the Data Fabric architecture.

These tools provide a unified platform to easily access and integrate data from multiple sources, while also providing data governance and security features. This makes it easier to ensure that data is managed in a compliant and secure manner, while allowing users to quickly access the data they need.

Data Fabric vs Data Mesh

Along with Data Fabric, Data Mesh is another approach that’s been gaining popularity in recent years. And there is often confusion over where they overlap, and where they differ.

Our CEO Sharad Varshney was recently asked this very question  at a Q&A, and this was his answer:

The easiest way to differentiate between a data fabric and a data mesh is this: A data fabric architecture is centered on integrating and connecting the technologies that support data management, and a data mesh architecture focuses on the people and procedures behind data management.

Both approaches streamline data management by connecting various systems and technologies in a distributed landscape. However, you could say that data fabric architecture effectively underpins a data mesh by providing the flexibility, agility, and connectivity required if domain owners are to support seamless, decentralized data access.

Essentially, the Data Fabric architecture is the foundation that makes it possible for domain owners to access and utilize data as part of a Data Mesh.


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