Data Fabric Market Size

Data Fabric Market Size

Data Fabric Market was valued at USD 2.4 billion in 2023 and is anticipated to grow at a CAGR of over 30% between 2024 and 2032. The rising digitalization and Artificial Intelligence (AI) integration into fabric data solutions is constantly enhancing scalability and agility. These platforms are dynamically adapting to changing data volumes, sources, and business requirements to support agile development and deployment of data-driven applications & services.

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For instance, in May 2023, Microsoft introduced Fabric, a comprehensive data and analytics platform distinct from Azure Service Fabric. The platform features integration tools, a Spark-powered data engineering platform with real-time analytics capabilities and enhanced Power BI for intuitive visualization and AI-driven analytics.
 

The increasing regulations and concerns about data privacy & security are significantly impacting the data fabric as there is a growing emphasis on enhancing consent management capabilities within the data fabric platforms. Organizations are implementing tools and workflows that enable transparent user consent for data collection, processing, and sharing activities. This ensures compliance with consent requirements outlined in data privacy regulations and builds trust with data subjects. Data fabric platforms are enhancing their audit and governance capabilities to demonstrate accountability and compliance with data privacy regulations.
 

Data fabric solutions often need to integrate data from different sources, which can increase complexity in data pipelines. This complexity leads to bottlenecks and latency issues, especially when dealing with larger volumes of data or real-time data streams. As data volumes grow and organizations up-scale their operations, data fabric platforms must support increasing demands for processing power and storage capacity. Ensuring seamless scalability across distributed environments, such as cloud and on-premises, without compromising performance is crucial and challenging. Organizations increasingly require real-time or near-real-time analytics capabilities to derive timely insights and respond to the ever-changing business conditions. Achieving low-latency data processing and analytics within data fabric environments is crucial for supporting these requirements effectively.