Data fabric

What is data fabric?

Data fabric is a modern data management architecture. It integrates and unifies data management, governance, and security across hybrid environments. The core idea behind this is to convert and combine a complex data background into a one-stop, smart, and real-time data management layer. Your IT and data team can easily manage everything in one place - from integration to analytics to governance.

Architecture and components

Data fabric is made of multiple layers, each with specific responsibilities.

Source layer: This represents the data sources across the organization, like on-premise storage, third-party databases and applications, data warehouses and lakes, SaaS applications, etc.

Metadata layer: Metadata is the data about your data itself. Metadata layer is crucial in data fabric as it manages data discovery, cataloging, quality checks, lineage tracking, and more.

Integration layer: This layer is about ETL and ELT workloads which connect and transform data from sources through batch processing or real-time streaming.

Security and governance: This is to enforce domain-specific and organization wide security standards and regulations. It takes care of encryption, access control, audits, authentication, and more across the universal data layer.

Consumption layer: This is the end user access layer, which is either a conventional SQL or a business intelligence tool. The final layer also supports AI/ML use cases so you could derive useful insights from your data. 

Benefits of data fabric

More flexibility: Despite managing disparate data sources, data fabric could help you adapt faster to changing business needs and evolving tech platforms.

Success with AI and ML: Data fabric brings you close to real-time analytics and data availability, which is crucial to run AI and Machine learning use cases.

Improved data access: Unify data sources from all corners and bring them into a universal data layer for seamless and on-time access. 

Cost effective: Cuts down the high maintenance costs of multiple data sources and reduces storage and infrastructure costs.

Unified governance: Despite your organization’s global distribution, number of divisions, and complex management, you could centralize governance management without limiting data utilization. 

Meta-data driven architecture: No need to organize manually data discovery, labeling, integration, and governance as data fabric uses a metadata approach to automate them.

High trust and reliability in data: Ensures that your entire organizational data sees one version of the truth and maintains consistency, which is crucial for data-driven decision-making.

Types of data fabric

Depending on the types of data sources you connect, data fabric can be of four types.

On-premise data fabric: primarily for on-premise data sources of organizations, for those who require strict control over their data or those who invested heavily in infrastructure and hardware.

Cloud data fabric: This type of data fabric integrates cloud platforms and databases like AWS, Azure, Google cloud etc, within a single cloud provider. It’s perfect for companies that want the flexibility and scalability of the cloud with a single provider or those who migrate their workloads to cloud. 

Multi-cloud fabric: Rather than integrating data sources from one cloud provider, this connects sources, each from a different cloud provider. With many companies relying on a multi-cloud strategy, this type can provide a great platform to manage data scattered across multiple providers.

Hybrid data fabric: This data fabric is a combination of both on-premise and single or multiple cloud data sources. Hybrid data fabric gives you the freedom to choose the best of tools and services for your business while keeping them integrated through a unified data layer.

AI-integrated data fabric: Here, you will have AI and automation integrated with every layer of the data fabric to simplify and automate integration tasks, trigger certain actions, receive actionable insights, and more.

Which organizations should use data fabric?

Data fabric is suitable for the following:

• Companies with complex data landscapes, multiple divisions and data sources.

• Companies with stringent compliance measures and regulations to adhere to.

• Companies that require real-time intelligence and become data-driven while supporting business decisions and operations.

• Large companies and enterprises struggling with hybrid or multi-cloud environments.

Build a custom and scalable enterprise data fabric layer with tools and technicians at your disposal. Get expert consultation from our team and implement a centralized data fabric layer in your organization.