Abstract: This case study introduces a new intelligent chatbot data analysis that aims to liberate data analysis by providing an intuitive and inclusive platform for users of all experiences. The chatbot allows users to easily upload CSV files and engage in natural language conversations to gain insights, generate insights, and derive predictive analysis. The project leverages the latest natural language processing (NLP) and machine learning (ML) technologies to help users interact seamlessly with the system. Users can ask questions, request specific information analysis, and seek clarification using the common language.
The approach involves collecting and prioritizing data, using powerful NLP models to understand language, and integrating machine learning algorithms for data analysis. The chatbot's interface is important for customer interest; It provides an intuitive environment for submitting information, user interaction, and approval. This AI-powered data analytics chatbot marks a major advancement in data analytics by bridging the gap between data intelligence and non-machine users. It simplifies data analysis, enabling a wider range of users to use intelligence capabilities to make data-driven decisions.
Keywords: NLP, Machine Learning, CSV File, Data Analytics, Data Processing, Data Visualization
Akshay Bhor, Ujwala Sangale, Abhishek Sinha, Aniket Shewale, Prof. Abhay Gaidhani" AI-Driven Insights and Data Visualization ", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 10, pp. 163-169, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121022
| DOI: 10.17148/IJARCCE.2023.121022