Synergistic Human-AI Collaboration: A Federated Approach to Enterprise Data Insights

This article introduces a novel architectural paradigm for enterprise data analytics: the Federated Data Insights Platform. Operating as an abstraction layer above distributed data ecosystems, this platform facilitates seamless collaboration between domain experts and artificial intelligence systems. By creating a symbiotic relationship between human contextual understanding and machine analytical capabilities, the platform addresses critical challenges in modern data management: governance enforcement, security maintenance, and the democratization of complex data analysis. The theoretical foundation integrates federated data management principles, cognitive augmentation theories, and organizational learning frameworks. The architecture encompasses an intelligent abstraction layer, modular AI components, collaborative interfaces, and embedded governance mechanisms. Implementation considerations span technical integration strategies, organizational adoption factors, and multidimensional evaluation metrics. The platform delivers interconnected benefits that collectively transform how enterprises derive value from distributed data assets.

Authors

Publication Details

Journal
European Modern Studies Journal
Published
2025-08-14
DOI
https://doi.org/10.59573/emsj.9(4).2025.47
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
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article

Synergistic Human-AI Collaboration: A Federated Approach to Enterprise Data Insights

Lakshmi Vara Prasad Adusumilli
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European Modern Studies Journal
Big Data and Business Intelligence
article

Synergistic Human-AI Collaboration: A Federated Approach to Enterprise Data Insights

Lakshmi Vara Prasad Adusumilli
article en

Abstract

This article introduces a novel architectural paradigm for enterprise data analytics: the Federated Data Insights Platform. Operating as an abstraction layer above distributed data ecosystems, this platform facilitates seamless collaboration between domain experts and artificial intelligence systems. By creating a symbiotic relationship between human contextual understanding and machine analytical capabilities, the platform addresses critical challenges in modern data management: governance enforcement, security maintenance, and the democratization of complex data analysis. The theoretical foundation integrates federated data management principles, cognitive augmentation theories, and organizational learning frameworks. The architecture encompasses an intelligent abstraction layer, modular AI components, collaborative interfaces, and embedded governance mechanisms. Implementation considerations span technical integration strategies, organizational adoption factors, and multidimensional evaluation metrics. The platform delivers interconnected benefits that collectively transform how enterprises derive value from distributed data assets.

European Modern Studies JournalVol. 9(4)
Openalex Percentile: Top 61%
Big Data and Business Intelligence
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