Generative AI-based Conversational Interfaces for Unified Data Catalog Navigation

  • Authors

    • Dr. Steven Young Professor, University of Washington, USA. Author
    • Dr. Rebecca Green Associate Professor, Arizona State University, USA. Author

    DOI:

    https://doi.org/10.67228/30715717/IJDEIC-2022PI3H7K

    Published 03-12-2022

  • Generative AI, Conversational Interfaces, Data Catalog Navigation, Unified Data Catalogs, Natural Language Processing, Data Management, AI-driven User Interaction, Metadata Discovery, Usability Testing, Data Governance

    Issue

    Vol. 5 No. 1 (2022)

    Section

    Articles

    How to Cite

    [1]
    S. Young and R. Green, “Generative AI-based Conversational Interfaces for Unified Data Catalog Navigation”, IJDEIC, vol. 5, no. 1, pp. 01–08, Mar. 2022, doi: 10.67228/30715717/IJDEIC-2022PI3H7K.

  • Abstract

    Data catalogs are essential tools for managing and discovering organizational data, but traditional navigation methods can be cumbersome, especially as data volumes grow. This paper explores the integration of generative AI-based conversational interfaces to enable intuitive and efficient navigation of unified data catalogs. By leveraging advanced natural language processing (NLP) models, users can interact with data catalogs through human-like dialogues, eliminating the need for complex query languages and manual search processes. We discuss the design, implementation, and evaluation of a conversational interface that provides users with real-time, context-aware responses to queries. Through a case study and usability testing, we demonstrate how such AI-powered systems enhance user experience, improve query accuracy, and streamline data discovery processes. Finally, we address the challenges and future directions of deploying generative AI in data catalog systems, emphasizing the need for scalable and secure solutions.

  • References

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