Project Overview: SQL Query Generation and Data Analysis

Features

• SQL Query Generation: Users can input questions related to data, and Gemini will generate the appropriate SQL queries to fetch relevant information from Google Cloud's BigQuery.
• Data Display: The results of the SQL queries are displayed in a dynamic table format, enabling users to easily explore and interact with the retrieved data.
• Post Selection and Analysis: After retrieving the data, users can select specific posts or data points by providing the post ID. The project will fetch additional content from the associated URLs and generate an in-depth analysis using AI.
• AI-Powered Insights: By leveraging Gemini's capabilities, the system not only generates SQL queries but also provides insights and analysis on the data, enabling deeper understanding and informed decision-making.

Workflow

1. User inputs a query, and Gemini generates the corresponding SQL query.
2. Data from BigQuery is fetched and displayed in a table.
3. User selects a post by ID, and the data from the post's URL is analyzed using Gemini.

This project combines advanced AI technology with cloud-based data processing, providing a seamless tool for both generating SQL queries and analyzing the data. The overall goal is to simplify data querying and analysis for users, making complex tasks more accessible and efficient.