As technologies advance, organisations are faced with a humongous load of data and struggle to use it effectively and still keep up with rapidly changing regulations.
According to Secureframe, in 2023 60% of executives revealed that their organisation invested more time and resources in complying with laws and regulations.
To manage such complexities from data analysis to data management and compliance, the concept of data fabric appeared – a framework that strives to simplify data for best use cases.
This article tells you everything you need to know about data fabric, what it is, its architecture, features and use cases.
What is Data Fabric?
Data fabric can be defined as a framework that connects vast amounts of data from different sources on a single platform and manages them efficiently. It offers a sustainable solution to organisations that are seeking a unified architecture to manage their data seamlessly on their cloud environments while still connecting to data pipelines on a single platform.
A data fabric intends to democratize and automate data management by bridging the gap between data producers and consumers through a single framework. This framework applies necessary governance policies and allows organisations to access and use all their data at any time safely.
It cuts through complexities posed by distributed architectures and prepares it for analytics, AI, and machine learning applications. The complexities are simplified through unification, cleansing, and securing the cloud environments while enabling organisations to optimise their data and scale their systems accordingly. The process simultaneously allows them to keep up with the rapidly changing markets.
Unlike data mesh, data fabric centres around developing a single, unified data layer on top of distributed data sources. Data mesh, however, uses a decentralised approach where data ownership and management are distributed to domain-specific teams within an organisation.
According to IBM, data fabric is an architecture that facilitates the end-to-end integration of various data pipelines and cloud environments through the use of intelligent and automated systems.
What is Data Fabric Architecture?
Data fabric architecture sources information from the data pipeline automatically to a unified platform. For instance, the information can be sourced from legacy systems like data lakes, data warehouses, SQL databases and application servers providing organisational operations overviews.
The data fabric architecture not only connects data pipelines to a unified platform but also simplifies the data to tackle the challenges of data gravity, data movement, transformation and integration.
IBM alludes to an example of a multi-cloud environment where a cloud like AWS manages data ingestion and another platform like Azure, oversees data transformation and consumption. There might be a third vendor like IBM Cloud Park for Data that provides analytical services. In such a case, the data fabric architecture stitches these environments together to create a unified view of data.
Data Fabric Features
1. Data democratisation
Data fabric breaks down data silos to make them accessible to a broad range of users with different applications within an organisation. This democratisation of data makes it possible to source relevant data faster to help executives make informed decisions across all levels of an organisation.
Through the data fabric’s unified platform and self-service tools for automation, the management framework equips analysts, data scientists, also non-technical users to access and interpret data without solely relying on IT specialists.
2. Unified data
Data fabric is a unified architecture that integrates and connects disparate data sources across an organisation. It creates a single source – a unified data layer where users can access all of their organisational data overcoming data silos.
This unified data layer facilitates data discovery, integration, and consumption, empowering users to derive valuable insights and make data-driven decisions. The data fabric leverages advanced technologies like metadata management, semantic layer, and machine learning to automatically discover, classify, and connect data, ensuring consistency and accuracy across the entire data landscape.
3. Cross-platform data management
Data fabric equips organisations with the capability to easily manage data across multiple platforms including on-premises systems, cloud environments, and edge devices. Through the data fabric’s unified platform, the solution simplifies the foundational complexities of data sources and technologies, presenting an opportunity to consolidate data from disparate sources.
This allows organisations to view and extract data from a single source creating consistency in operations, and improving data accessibility, and governance, ultimately equipping organisations with the ability to make more informed decisions and drive innovation.
4. Governance
Data fabric provides an essential feature to integrate real-time governance policies into sourcing and managing data. This ensures that organisations are aligned with the data governance policies and enforce them continuously across disparate data pipelines.
To ensure governance, data fabric automates data lineage tracking, metadata management, and access controls. This allows organisations to maintain integrity and protect sensitive information. It also facilitates data auditing and compliance reporting, ensuring adherence to industry regulations and internal standards.
With data fabric, organisations can establish a culture of data governance, enabling users to make informed decisions while mitigating risks and safeguarding valuable data assets.
Use cases
1. Financial Service Compliance
Data fabric is highly beneficial for organisations to integrate into their cloud environments especially when dealing with vast amounts of data. This helps them keep up with numerous regulations that are often updated or changed from the local level to national and international levels.
For instance, financial service industries have some of the highest compliance costs with the average cost of compliance equalling $30.9 million according to Hyperproof.
Integrating a data fabric into financial companies’ cloud environments could help them stay on top of compliance complexities, ultimately reducing litigation expenditure and boosting efficiency.
2. Sales prediction
Data fabric can benefit sales teams of different organisations immensely by allowing these users to analyse complex and huge data sets for curating reliable forecasts. This would also allow them to access untapped data and leverage it for a variety of possibilities.
For instance, they can check expenditure spikes quickly and take action to minimise them by further probing the system to understand the cause of the spike. Organisations as a result can allocate resources accordingly and also be prepared for future spikes and dips.
