Do I need to change from Data Fabric to Data Mesh?
The hype about Data Mesh continues to grow, and innovative companies seek to implement the approach to their data management systems. One might ask the question: What about the data architecture we already have in place? Do we need to say goodbye to Data Fabric now? As Gartner® states in the Hype Cycle for Data Management 2023: “Several technologies and disciplines around future data architectures are currently heading into or passing through the trough: DataOps, data fabric, active metadata management, and augmented data cataloging/metadata management solutions”—stating that database features are moving towards “obsolete before plateau”. But this doesn’t mean that Data Fabric is less functional today. Gartner® rather assumes that the functions of Data Fabric will converge with Data Mesh.
The objective is the same: Greater access and use of more of the company’s data.
While one might believe Data Mesh and Data Fabric are opposing approaches, they ultimately pursue the same goal of improving data management. Data Mesh focuses on decentralized responsibility and collaboration, whereas Data Fabric focuses on a unified infrastructure and data integration. – Source
Differences between Data Mesh vs. Data Fabric
Data Mesh and Data Fabric are both concepts designed to address challenges in the modern data landscape, particularly as organizations grow in complexity and scale. While they share some overlapping principles, they are distinct in their approach and focus.
Whether you choose Data Fabric, Data Mesh, or a blend of both will depend on your specific needs and requirements—and the considerations for the architectures and technologies you already have in place. Data Mesh is about rethinking organizational structures and responsibilities around data, while Data Fabric is about creating a unified technological layer for data access and integration.
Whatever data architecture you prefer or already have in place, the AI-powered Data Product Builder complements your existing technology ecosystem and enables your team to expedite the ability to connect, discover, prep, quality check and deploy ready to use data products for business consumption.
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Your Contact: Sebastian Wernicke | Leading Data Scientist
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