MECHANICSBURG, PA, December 29, 2025 /24-7PressRelease/ -- The paper introduces a Fabric-first lakehouse architecture designed to help enterprises scale analytics and GenAI while maintaining unified governance across data and AI workloads. The framework positions Microsoft Fabric as the governance-centric analytics control plane, OneLake as a unified data foundation to reduce duplication, and Databricks as an execution layer for compute-intensive analytics, ML, and GenAI workflows.

In aligned enterprise implementations, Peram reports a 40% improvement in data-to-model readiness latency and a 60% improvement in AI system reliability, measured by fewer Databricks Model Serving endpoint errors/timeouts, improving production stability under real-world traffic variability.

Contact: Purnimanand Peram | [email protected]

LinkedIn: www.linkedin.com/in/purnimanand-peram-b21112118

IJETR_Article: https://iaeme.com/Home/article_id/IJETR_10_02_004

About IJETR: The International Journal of Engineering and Technology Research (IJETR) publishes research across engineering and technology domains. This release references the published article "A Fabric-First Lakehouse Architecture: A Comprehensive Framework for Scalable Analytics and Generative AI" (DOI: 10.34218/IJETR_10_02_004).

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