Generative AI for Automated Data Analysis and Insight Generation

1ST Sathvika A

Assistant professor of department AI&DS

Annamacharya institute of technology and sciences Tirupati,India

andesathvika2602@gmail.com

2th P Joseph Prasanth

Dept of AIDS Annamacharya institute of technology and sciences Tirupati,India josephprasanthreddy@gmail.com

4th Indravathi E

Dept of AIDS Annamacharya institute of technology and sciences Tirupati,India

emaniindira6@gmail.com

5th Somasankar Naik A

Dept of AIDS Annamacharya institute of technology and sciences Tirupati,India asankarnaik921@gmail.com

3th Charan Kumar S

Dept of AIDS Annamacharya institute of technology and sciences Tirupati,India sriramulacharankumar24@gmail.com

Abstract--Data analysis constitutes a significant part of data science and machine learning with the rapid expansion of digital data to assist in decision making particularly. Data exploration and selection of appropriate machine learning models can however be tedious and require high level of expertise. This study suggests the Automated Data Analyzer which is an easy tool of Insight Creation on the dataset. The system is coded in Python and Streamlit framework and enables Google Gemini to form conclusions and suggest machine learning algorithms. The application is easy to use since all one has to do is input a dataset and the data is subsequently preprocessed, visualized, and analyzed. When dealing with large number of data, Principal Component Analysis (PCA) is used in order to compress the number of dimensions in preserving important information and hence making the analysis faster and more efficient. Statistical analysis of the system is also done to comprehend distribution of data. The insights and the visualizations are stored in an SQLite database, and a final report is created that contains insights, the visualizations and model suggestions. This method assists in the automation of the Exploratory Data Analysis (EDA).

Keywords— Exploratory Data Analysis (EDA), Generative AI, Machine Learning, Data Visualization, Anomaly Detection, PCA, Statistical Analysis, AI-driven Insights.