ESC Dashboard

Analytics Dashboard for the Empowerment Student Center

A proposed solution to transform Qualtrics survey data into actionable visualizations and statistics.

The application is in the planning and design phase (Sprint 0/1). No real functional code has been implemented yet. This README serves as our development roadmap and specification document.

Project Vision

The Problem

The Empowerment Student Center (ESC) faculty member currently spends hours manually analyzing alumni exit survey data exported from Qualtrics. This multi-step process involves:

1. Exporting CSV from Qualtrics
2. Manually analyzing data in Excel
3. Creating charts one-by-one
4. Calculating statistics manually
5. Formatting for presentations

This process is time-consuming and prevents staff from focusing on interpretation and strategic planning.

Our Proposed Solution

The ESC Dashboard would be a web application that:

• Accepts CSV files exported from Qualtrics
• Helps user pick question types
• Generates appropriate visualizations
• Calculates relevant statistics
• Provides interactive filtering and customization

Goal: Reduce multi-hour analysis process to minutes.

Why This Approach

• User-Friendly - Designed for administrators without technical backgrounds
• Proposal-Ready - Would help generate publication-quality outputs for funding proposals
• All-in-One - Single application combining parsing, visualization, and export

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Proposed Features

Core Functionality (Planned)

• Automatic CSV Upload - One-click import of Qualtrics exports
• Dynamic Visualizations - Appropriate chart generation based on question type selected:
  • Multiple Choice → Pie charts or bar charts with percentages
  • Likert Scale → Stacked bar charts showing distribution
  • Numeric → Histograms or box plots with mean/median
  • Open-Ended Text → Word clouds showing common themes
• Statistical Analysis - Automatic calculation of means, medians, percentages, and other statistics depending on question type
• Advanced Filtering - Ability to filter by demographics, date ranges, and variables

Potential Future Features (Stretch Goals)

• Custom chart styling and color schemes
• Save/load dashboard configurations
• An ability for Susan to save data

Note: we are currently trying to have a small prototype for Susan so we can better understand what she needs

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Planned Tech Stack

These technologies have been selected for the project but not yet implemented.

Frontend (Proposed)

• DJango - Component-based UI framework
  • Why: Familiar to team, good for dashboard interfaces

Backend (Proposed)

• Python 3.11+ - Core language
  • Why: Strong data science ecosystem
• Flask or FastAPI - Web framework
  • Decision pending: Flask (simpler) vs FastAPI (better docs/performance)
• Pandas - Data manipulation
  • Why: Industry standard for data analysis
• Matplotlib/Plotly - Chart generation
  • Decision pending: Static (Matplotlib) vs Interactive (Plotly)

Deployment (Proposed)

• Vercel - Frontend hosting (free tier)
• Render - Backend hosting (free tier)
• GitHub - Version control

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Intended Usage

This describes how the application would work when implemented.

For End Users (Theoretical)

System Requirements

• Modern web browser (Chrome, Firefox, Safari, Edge)
• Internet connection
• JavaScript enabled

Planned Access Method

1. Navigate to: https://esc-dashboard.vercel.app (not yet deployed)
2. No installation or login required
3. Bookmark for easy access

Note: On free-tier hosting, first page load after 15+ minutes of inactivity may take 30-60 seconds for server to "wake up."

Proposed User Workflow

Step 1: Export from Qualtrics

1. Log into Qualtrics
2. Open survey → Data & Analysis tab
3. Export & Import → Export Data
4. Select CSV format
5. Download file

Step 2: Upload CSV (Theoretical)

• Click "Upload CSV" or drag-and-drop file
• System processes (estimated 5-15 seconds)
• Preview data and parse questions

Step 3: View Visualizations (Theoretical)

• System automatically detects question types
• Generates appropriate charts
• Calculates statistics
• Displays interactive dashboard

Step 4: Filter Data (Planned Feature)

• Filter by demographics, dates, subgroups
• Visualizations update automatically

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Proposed System Architecture

These diagrams represent our planned architecture, not implemented code.

Conceptual Component Diagram

┌─────────────────────────────────────────────────────────┐
│                User Interface (Planned)                 │
│                    (Django)                             │
├──────────────┬──────────────┬──────────────┬────────────┤
│   Upload     │  Dashboard   │   Filter     │   Export   │
│  Component   │  Component   │  Component   │ Component  │
│  (Not built) │ (Not built)  │ (Not built)  │  (stretch) │
└──────┬───────┴──────┬───────┴──────┬───────┴─────┬──────┘
       │              │              │             │
       └──────────────┴──────────────┴─────────────┘
                      │
                      │
       ┌──────────────┴──────────────┐
       │                             │
┌──────▼─────────┐         ┌─────────▼────────┐
│   CSV parser   │         │  Visualization   │
│    Service     │         │     Service      │
│  (Proposed)    │         │   (Proposed)     │
└──────┬─────────┘         └─────────┬────────┘
       │                             │
       └──────────────┬──────────────┘
                      │
              ┌───────▼────────┐
              │  Data Analysis │
              │    Service     │
              │   (Proposed)   │
              └────────────────┘

Theoretical Data Flow

User
 │
 │ 1. Would upload CSV
 ▼
Frontend (To be built)
 │
 │ 2. Would send CSV file via API
 ▼
Backend API (To be built)
 │
 │ 3. Would help parse & analyze
 ▼
CSV Parser → Question Selector (Both planned)
 │
 │ 4. Would generate visualizations
 ▼
Chart Generator (Planned)
 │
 │ 5. Would return data + charts
 ▼
Frontend Display (To be built)
 │
 │ 6. Would show dashboard
 ▼
User views results

Hypothetical CSV Upload Flow

User          Frontend        Backend         Parser         Analyzer      Chart Gen
 │               │              │              │               │              │
 │ Upload CSV    │              │              │               │              │
 ├──────────────▶│              │              │               │              │
 │         (theoretical)        │              │               │              │
 │               │ POST /upload │              │               │              │
 │               ├─────────────▶│              │               │              │
 │               │        (to be implemented)  │               │              │
 │               │              │ Parse CSV    │               │              │
 │               │              ├─────────────▶│               │              │
 │               │              │        (planned logic)       │              │
 │               │              │              │ Question types│              │
 │               │              │              ├──────────────▶│              │
 │               │              │              │        (to be built)         │
 │               │              │              │               │ Generate     │
 │               │              │              │               │ charts       │
 │               │              │              │               ├─────────────▶│
 │               │              │              │               │  (planned)   │
 │               │              │◀─────────────┴───────────────┴──────────────┘
 │               │              │ Return JSON (would happen here)
 │               │◀─────────────┤
 │ Display       │              │
 │ Dashboard     │              │
 │◀──────────────┤              │

(All arrows represent planned functionality, not implemented code)

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Hypothetical Setup Instructions

These will work once code is implemented:

Frontend (Not yet available):

cd frontend
npm install          # Dependencies don't exist yet
npm run dev          # No dev server to run yet

Backend (Not yet available):

cd backend
python -m venv venv           # Can create, but no code to run
source venv/bin/activate
pip install -r requirements.txt  # File doesn't exist yet
flask run --debug             # No Flask app to run yet

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Contact & Support

Project Team

• Ari - Backend Development, Data Science
  • Email: osmunjai@gmail.com
• Howl - Frontend Development, UX Design
  • Email: howlhund@gmail.com

Client

• Susan - Empowerment Student Center
• Organization: Montana State University

Report Issues (When Application Exists)

For End Users:

• Email the team with:
  • Description of what you tried to do
  • What happened vs. what you expected
  • Error messages
  • Screenshots

For Developers:

• GitHub Issues (when repository is public)
• Bug report template (to be created)