AI-Driven Customer Intelligence in Enterprise Lakehouse Systems Sentiment Mining Governance-Aware Analytics and Real-Time Data Synchronization
Abstract
The rapid growth of digital interactions across enterprise ecosystems has generated massive volumes of structured and unstructured customer data. Organizations increasingly adopt lakehouse architectures to unify data warehousing and data lake capabilities, enabling scalable analytics and artificial intelligence (AI)-driven insights. This research explores AI-driven customer intelligence within enterprise lakehouse systems, emphasizing sentiment mining, governance-aware analytics, and real-time data synchronization. By integrating natural language processing (NLP), machine learning models, and streaming pipelines, enterprises can derive actionable insights from customer feedback, transactional data, and behavioral patterns. Governance-aware analytics ensures regulatory compliance, data privacy, lineage tracking, and ethical AI deployment within centralized data platforms. Real-time synchronization frameworks enable consistent data availability across operational and analytical systems, supporting timely decision-making. The study proposes a comprehensive architecture that integrates ingestion pipelines, unified metadata governance, AI model orchestration, and streaming analytics for enterprise-scale deployments. Experimental validation demonstrates improved sentiment classification accuracy, enhanced compliance visibility, and reduced latency in cross-system data updates. The findings suggest that lakehouse-based AI intelligence frameworks significantly enhance personalization, operational efficiency, and strategic decision-making while maintaining governance and data integrity standards in distributed enterprise environments.
Article Information
Journal |
International Journal of Advanced Engineering Science and Information Technology (IJAESIT) |
|---|---|
Volume (Issue) |
Vol. 7 No. 5 (2024): International Journal of Advanced Engineering Science and Information Technology (IJAESIT) |
DOI |
|
Pages |
14898-14905 |
Published |
September 8, 2024 |
| Copyright | |
Open Access |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
How to Cite |
Dr. S. Jagadeesh Soundappan (2024). AI-Driven Customer Intelligence in Enterprise Lakehouse Systems Sentiment Mining Governance-Aware Analytics and Real-Time Data Synchronization. International Journal of Advanced Engineering Science and Information Technology (IJAESIT) , Vol. 7 No. 5 (2024): International Journal of Advanced Engineering Science and Information Technology (IJAESIT) , pp. 14898-14905. https://doi.org/10.15662/IJAESIT.2024.0705006 |
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