The global data fabric market is valued at USD 3.55 billion in 2025 and is projected to reach USD 17.02 billion by 2032, expanding at a striking 25.1% CAGR. What was once a specialized architecture for large enterprises is rapidly becoming a foundational layer for organizations navigating hybrid clouds, real-time analytics, and AI-driven decision-making. As companies deal with exploding data volumes, distributed systems, and rising governance demands, data fabric solutions are emerging as the “connective tissue” that unifies disparate data environments into a single, intelligent data ecosystem.
AI adoption, accelerated cloud migration, and real-time workloads moving to the edge drive the shift across banking, healthcare, manufacturing, telecom, and retail industries. These trends are reshaping how organizations store, access, govern, and utilize data for both operational and analytical purposes.
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Market Size & Growth Rate: Data Fabric Goes Mainstream as AI Demands Better Data Infrastructure
Data fabric is rapidly moving from early experimentation to full-scale enterprise deployment as organizations modernize legacy systems and expand AI/ML workloads. With digital transformation spending accelerating worldwide, the market growth reflects a decisive shift toward architectures that deliver unified metadata management, automated orchestration, and seamless data virtualization across hybrid and multi-cloud environments.
In May 2023, Informatica became one of the first ISV partners for Microsoft Fabric, integrating its Intelligent Data Management Cloud (IDMC) to provide automated cataloging, integrated pipelines, and AI-driven data quality directly within Microsoft’s ecosystem—significantly speeding up enterprise data modernization.
Data fabric architectures address major barriers to AI by enabling real-time data integration, automated metadata discovery, and intelligent governance across distributed systems. Industries such as BFSI and telecom—where fraud detection, analytics, and customer experience rely on high-volume, low-latency data—are increasingly adopting data fabric to support real-time decision models. As applications like fraud scoring, predictive maintenance, and hyper-personalization expand, the need for a unified and governed data infrastructure is becoming essential.
In June 2024, SAP explained in its whitepaper “Business data fabric: The future of data and AI,” how SAP Datasphere simplifies distributed data landscapes and provides consistent, governed access to insights, reinforcing data fabric as a core enabler of modern AI workloads.
(Sources: Informatica and SAP)
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Key Technology Trend: AI-Enhanced Data Fabric Takes Center Stage
AI-augmented data management is emerging as a key technology trend, with modern data fabric platforms embedding machine learning for metadata discovery, anomaly detection, schema matching, and automated lineage tracking. These capabilities significantly reduce manual data engineering effort as enterprise data continues to expand across SaaS applications, private clouds, and on-premise systems.
Active metadata intelligence is also becoming standard, allowing systems to automatically map relationships, flag anomalies, and recommend governance rules—creating a more dynamic, self-optimizing data ecosystem. Vendors such as Informatica, IBM, Talend, SAP, and Denodo are incorporating AI copilots to support data preparation, quality validation, and pipeline automation, making advanced data management accessible to broader teams.
In March 2024, SAP advanced this trend by introducing new AI-driven capabilities for Datasphere, including generative AI enhancements, knowledge-graph support, and improved governance features. It reinforced the industry's move toward metadata-rich, AI-ready data fabric architectures.
(Source: SAP)
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Cloud & Edge Adoption: Hybrid Data Fabric Becomes the Enterprise Default
Hybrid and multi-cloud strategies now dominate enterprise IT plans, making data fabric the preferred architecture for connecting distributed environments. Organizations want the flexibility of AWS, Azure, Google Cloud, and private cloud systems without dealing with data silos or inconsistent governance. As cloud migration accelerates, data fabric unifies data across on-premise, cloud, and edge environments, removes redundant integration layers, and ensures high-speed access for AI workloads.
Edge computing is also reshaping data needs across manufacturing, logistics, telecom, and autonomous systems. With more processing occurring near devices and sensors, data fabric synchronizes edge and cloud data, enabling continuous data flow and real-time AI-driven insights.
(Source: FREEPIK)
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Innovation Trends: Metadata Automation, Security Intelligence, and Low-Code Integration
Innovation in data fabric is accelerating as enterprises push for faster data activation and improved governance. Metadata-driven automation is becoming standard, using machine learning to detect data quality issues, monitor pipelines, and flag anomalies with minimal manual effort. At the same time, rising cybersecurity demands are driving the adoption of zero-trust data governance with fine-grained access controls and real-time threat monitoring.
Low-code and no-code tools are expanding access to data integration, while semantic layers help standardize business metrics. As a result, organizations increasingly prefer transparent, automated, and easy-to-manage data fabric solutions over complex, manually supported systems.
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Future Outlook: AI-Driven Personalization & Autonomous Data Pipelines
AI will gradually move data fabric toward autonomous operation, where mapping, governance, and orchestration adjust dynamically. This evolution will support real-time personalization across industries by enabling fast, context-aware insights.
Digital twins, IoT systems, and AI-powered recommendation engines will rely on unified, high-quality data streams delivered through data fabrics. As subscription-based cloud services expand access for mid-sized enterprises, data fabric will become a standard architectural layer.
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