Enhancing Data Insightsthrough LIDA-Streamlit Integration
Akshay Bhor, Ujwala Sangale, Abhishek Kumar Sinha, Aniket Shewale, Prof. Abhay Gaidhani · IJARCCE · 2024
The research paper explores the realm of AI-driven insights and data visualization, focusing on the utilization of LIDA (Language-Integrated Data Analysis) as a powerful tool for facilitating data analytics.In today's data-centric world, the ability to extract meaningful insights and communicate them effectively is paramount for informed decision-making.Our project aims to democratize the field of data analysis by providing an intuitive and inclusive platform accessible to users of all technical backgrounds.LIDA leverages cutting-edge Natural Language Processing (NLP) and Machine Learning (ML) techniques to enable users to effortlessly upload CSV files and engage in natural language conversations to extract insights, generate visualizations, and receive predictive analytics.The methodology encompasses comprehensive data collection and preprocessing, deploying robust NLP models for language comprehension, and integrating ML algorithms for data analysis.The chatbot's interface prioritizes userfriendliness, offering an intuitive environment for data upload, user interactions, and actionable insights.Through realworld case studies and examples, we demonstrate the effectiveness of LIDA in generating actionable insights and facilitating data-driven decision-making.The research contributes to bridging the gap between data expertise and nontechnical users, empowering a broader user base to harness the potential of artificial intelligence in data analytics.