📊 CVOTER Survey Data Dashboard

This is a web-based dashboard created during my internship at CVOTER, designed to display, sort, and visualize large-scale survey data using modern web technologies. The project connects an Excel-based dataset to a Microsoft SQL Server backend and uses Flask to serve dynamic content including tables and interactive charts powered by Highcharts.

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🚀 Features

• 📥 Automated Data Ingestion from Excel to MS SQL Server
• 🗃️ Dynamic Database Schema Creation using SQLAlchemy
• 📄 Paginated Data Table View with sorting options
• 📈 Interactive Satisfaction Trend Chart using Highcharts
• 🔍 Custom Views:
  • Most satisfied respondents
  • Least satisfied respondents
  • Latest and oldest survey entries
• 🌐 Responsive and Clean UI using HTML, CSS, and JS
• 📊 Real-time data visualization over time across 8500+ entries

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🧠 Skills & Technologies Learned

During this project, I worked with and gained hands-on experience in:

• Python (Flask) – Web development and backend routing
• MS SQL Server – Handling and querying large structured datasets
• SQLAlchemy – ORM for seamless interaction between Python and SQL
• Pandas – Data preprocessing and manipulation from Excel files
• Highcharts – Building real-time, interactive graphs
• HTML/CSS/JavaScript – Frontend templating and interactivity
• Jinja2 – Dynamically rendering HTML with Flask backend

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🗂️ Project Structure

📁 project-root/
├── main.py                  # Flask backend logic
├── data.xlsx                # Raw survey data source
├── templates/
│   └── index.html           # Main UI template
├── static/
│   └── style.css            # Custom CSS styles
└── README.md                # This file

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📌 How It Works

1. Data Ingestion:

   • Loads data from data.xlsx using pandas.
   • Dynamically creates a SQLAlchemy model based on the Excel columns and data types.
   • Initializes a MS SQL Server database and stores the entire dataset.

2. Web Interface:

   • A home route (/) displays a paginated table of all responses.
   • Sorting routes (/msatisfied, /lsatisfied, /latest, /oldest) display sorted subsets of data.

3. Data Visualization:

   • The / route also renders a Highcharts line graph to track satisfaction levels over time.
   • The chart includes four series:
     • Very much satisfied
     • Satisfied to some extent
     • Not at all satisfied
     • Don't Know/Can’t say

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⚙️ How to Run Locally

1. Install Dependencies

   pip install flask flask_sqlalchemy pandas openpyxl pyodbc
   

2. Ensure MS SQL Server is Running

   • Update the database URI in main.py if needed:

     app.config["SQLALCHEMY_DATABASE_URI"] = "mssql+pyodbc://<username>:<password>@<server>/<db_name>?driver=ODBC+Driver+17+for+SQL+Server"

3. Run the App

   python main.py

4. Open your browser at http://127.0.0.1:5000/

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Screenshots

Sorted by most satisfied

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🧑‍💻 Author

Parantap Mishra Intern – CVOTER LinkedIn • GitHub