What is a data fabric?
Data fabric is defined as an integrated data architecture that encompasses data management processes and facilitates end-to-end integration of numerous data pipelines in an organization. It is an architecture that helps standardize numerous data management processes across several environments, such as on-premises or in the cloud. It can be deployed “anywhere”, which includes cloud (hybrid, public, and private cloud), on-premises, edge, and IoT devices. Data fabric helps ensure consistency across various integrated environments.
Benefits of using data fabric
A few benefits of data fabric include:
- Increased visibility across the data landscape: Since data fabric is a unified platform, it provides its users with greater visibility into the highly complex, heterogeneous data landscape across an organization.
- Deep-dive analytics and insights: Since data fabric helps connect several data pipelines across the organizations and provides complete visibility, it makes it easier for data users to control and manage data, allowing more effective insights to help drive data-backed business decisions. This helps businesses become more “data-driven” and provide a solid rationale for any business decisions.
- Use cases across the organizations: Data fabric can benefit almost all departments within a business and is not limited to a select few. Fraud detection and security management, governance and compliance teams, sales and marketing departments, engineering departments, etc., can all make use of data fabric platforms.
- Optimization: Data fabric platforms help monitor and observe storage costs (on a hybrid cloud or on-premises), helping improve overall efficiency. Companies can decide to scale up/down based on the insights received and focus on resource optimization.
Basic elements of a data fabric
It is essential to identify the fundamental elements of data fabric. A few of them are listed below:
- Knowledge graph: A knowledge graph is a type of data representation that uses graphs to identify interlinks, relationships, and connections. Since the core of data fabric is dependent on integrations, a data fabric software should be able to create a knowledge graph that can connect numerous disparate data sources.
- Integration capabilities: Data fabric platforms should be able to integrate various data pipelines. This includes the ability to extract, transform, and manage data to ensure performance efficiency.
- Data governance: Data policies, data governance, and data compliance must be followed when building data integrations.
- Data lifecycle management: Data fabric should oversee the end-to-end data lifecycle management.
- Cloud support: Data fabric platforms should be able to run on-premises as well as in cloud environments.
- Analytical tools support: Since data fabric is aimed at providing clean and complete data, a suitable data fabric platform should have some analytical capabilities or connectivity to other analytical tools.
Data fabric vs. data mesh
Data fabric is often confused with data mesh, but the two have a few fundamental differences. Although both software relate to data management architecture and its integration, the difference is that data mesh involves a human component—delivering data to people and teams specific to the business domain. It adapts the concept of “data as a product”, which means different teams will only handle the data in their pipeline. It is highly decentralized and ensures that each domain remains accountable for their data pipeline. Data fabric, on the other hand, enables any data from any location to be extracted, transformed, and worked upon and encompasses the entire data lifecycle.
Preethica Furtado
Preethica is a Market Research Manager and Senior Market Research Analyst at G2 focused on the data and cloud management space. Prior to joining G2, Preethica spent three years in market research for enterprise systems, cloud forecasting, and workstations. She has written research reports for both the semiconductor and telecommunication industries. Her interest in technology led her to combine that with building a challenging career. She enjoys reading, writing blogs and poems, and traveling in her free time.
