EDA Studio
Intelligent Dataset Explorer
Built a full-stack exploratory data analysis dashboard that turns uploaded CSV, TSV, and JSON datasets into statistical profiles, interactive Plotly charts, correlation insights, sortable tables, and generated notebook-style analysis.
System Architecture
Full-stack exploratory-analysis flow implemented in EDA Studio.
Multi-format upload
CSV, TSV, or JSON files up to 50 MB enter the browser-based analysis workspace.
Type + quality scan
Columns, nulls, uniqueness, descriptive statistics, and inferred types are summarized.
Interactive visual analysis
Plotly charts, correlation views, filters, and sortable tables support rapid exploration.
Analysis workspace
Selected views and findings are arranged into a notebook-style investigation flow.
Reusable sessions
Project and analysis state are organized through the application data layer for repeat visits.
Interactive statistical profiles and visual evidence for uploaded datasets.
Project Overview
EDA Studio is a full-stack exploratory data analysis platform designed to help users understand raw datasets through an interactive dashboard workflow.
The application supports CSV, TSV, and JSON uploads, parses files server-side, and turns the data into overview cards, descriptive statistics, distributions, correlation heatmaps, pattern insights, raw-data tables, and notebook-style analysis output.
The frontend is built with Next.js, TypeScript, Tailwind CSS, Framer Motion, Plotly.js, and TanStack Table, giving the dashboard animated transitions, rich charts, sortable and paginated data tables, and a polished upload-to-insight experience.
The architecture includes Next.js Route Handlers for upload and analysis sessions, a pure TypeScript analysis engine, notebook generation utilities, and Prisma/PostgreSQL support for saving recent analysis sessions.
The project is deployed on Vercel as a live data exploration tool, making automated EDA accessible without requiring users to write analysis code first.
Problem
Exploratory data analysis often requires repetitive setup before users can inspect distributions, correlations, missing values, summary statistics, and raw records.
Solution
Built a Next.js analytics dashboard that accepts common dataset formats, runs reusable TypeScript analysis logic, and presents the results through interactive charts, tables, insights, and generated notebook-style code.