Conversational AI for Enterprise Data Analytics and Governance: A Comprehensive Framework for Natural Language-Driven Business Intelligence
DOI:
https://doi.org/10.32628/CSEIT25111329Keywords:
Conversational AI, Enterprise Analytics, Data Governance, Natural Language Processing, Large Language Models, Business Intelligence, Human-Computer Interaction, Data DemocratizationAbstract
The integration of conversational artificial intelligence into enterprise data analytics and governance represents a paradigm shift in how organizations interact with their data assets. This paper presents a comprehensive framework for implementing conversational AI systems that enable natural language querying, automated compliance monitoring, and intelligent data discovery in enterprise environments. The proposed architecture leverages advanced natural language processing techniques, including large language models and context-aware dialogue systems, to bridge the gap between business users and complex data infrastructures. Through empirical evaluation across three enterprise domains— financial services, healthcare, and telecommunications—the framework demonstrates significant improvements in query response time (67% reduction), user adoption rates (89% increase), and data governance compliance (78% improvement). The system addresses critical challenges including query ambiguity resolution, multi-modal data integration, and real-time governance policy enforcement. Results indicate that conversational AI can effectively democratize data access while maintaining stringent security and compliance requirements, positioning it as a transformative technology for enterprise data management.
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