# School Scheduling System Upgrade

From Spreadsheets to AI-Ready Database

AI Technology Project Presentation
Student Researcher: Березуцкий Григорий Алексеевич
Supervisor: Bob Santos
January 2026

# The Core Problem: Spreadsheet Limitations

School schedules maintained in spreadsheet formats present challenges for efficient management and querying.

### Current System Limitations

- Data Duplication: Student information, teacher details, and class schedules repeated across multiple spreadsheets
- Inefficient Queries: Finding specific schedule information requires manual searching and complex formula calculations
- Data Inconsistency: Updates in one spreadsheet often don't propagate to related schedules, leading to conflicting information
- Limited Accessibility: Spreadsheets cannot provide real-time, personalized schedule information to students

### Operational Impact

- Administrative staff spend significant time reconciling schedule information
- A room change requires updates in multiple spreadsheet files
- Parents and students lack access to real-time schedule information
- Manual searching for student locations takes 5-10 minutes

# Project Goals

Transform spreadsheet-based scheduling into database solutions.

Eliminate Data Duplication

Create single source of truth for all scheduling data

Enable Efficient Queries

Answer "Where is student X?" in less than 1 second

Ensure Data Consistency

Automated validation and synchronization across all data

Provide Mobile Access

Real-time schedule information for students, parents, and staff

### Performance Objectives

- 90% reduction in data entry time
- 100% elimination of duplicate data entry
- Real-time query response: < 1 second
- Support for 1,000+ concurrent users

# Method: Systematic Approach

Structured methodology to address spreadsheet limitations.

1
Analyze Current System
Map data duplication and inconsistency points across existing spreadsheets
2
Design Database Structure
Create normalized schema to eliminate redundancy and ensure data integrity
3
Develop Migration Tools
Build Python scripts to extract and transform spreadsheet data into database format
4
Create Query Interface
Develop Telegram bot and API for real-time schedule queries
5
Implement Validation
Add data consistency checks and audit logging to prevent future issues

# School Schedule Complexity Analysis

School timetables involve overlapping systems that challenge spreadsheet management.

### Key Structural Elements

Complex Groupings: Students in multiple groups simultaneously
Temporal Structure: Two modules with different schedules
Multiple Dimensions: 5+ simultaneous student affiliations

### Student Group Types

- Primary class groups (e.g. 4A, 4B, 4C) - Maintained in separate files
- English proficiency groups (E1-E6) - Separate spreadsheet for each level
- Technology track groups - Additional spreadsheet file
- Olympiad groups - Separate tracking spreadsheet
- Extracurricular activities - Additional schedule files

Current Process: A single student's schedule requires checking multiple spreadsheets. Our database solution consolidates everything into unified queries.

# System Architecture: DFD & ERD

Complete diagrams showing database system design.

Data Flow Diagram (DFD)
DFD: System Workflow

Interactive workflow showing data flow from spreadsheets into unified database

### DFD System Features

- Centralized data flow - Consolidated data management
- Automated synchronization - Updates propagate instantly
- Single source of truth - Eliminates duplicate entries
- Real-time validation - Data integrity checks

Entity Relationship Diagram (ERD)
ERD: Database Structure

Database structure designed to address spreadsheet limitations

### Core Database Tables

- students, teachers, subjects - Centralized entity management
- schedule_entries - Unified scheduling table
- relationship tables - Structured data relationships
- audit_log - Comprehensive change tracking

# Database Design: 17 Tables

Normalized structure designed to handle scheduling complexity.

Security Layer
users – Controlled access system
audit_log – Comprehensive change tracking
Core Data
people – Students & Teachers
places – Rooms & Equipment
groups – Classes & Activities
Connection Hub
schedule_entries – Central connection point
time_management – Timeslots & scheduling
special_groups – Tech tracks & English levels

### Database Design Approach

Current System: Multiple spreadsheet files with duplicated data

Proposed System: 17 connected database tables with normalized structure

All data connects through the Schedule Entries table, replacing manual spreadsheet cross-referencing.

# Functional Prototype

Telegram bot demonstrating query efficiency improvements.

### Query Demonstration

/whereis
Please enter student name:
Гаттарова София
София: Room 204, Design & Creativity, Ms. Smith (10:30-11:15)
1
/whereis Command
Checks student location by time and group memberships
2
/schedule Command
Shows complete daily schedule
3
/tomorrow Command
Displays tomorrow's schedule

### Query Efficiency Comparison

- Manual Spreadsheet Method: 5-10 minutes across multiple files
- Database System: Less than 1 second response time

# Technology Stack

Tools selected for system implementation.

Python Programming
Telegram Bot Platform
SQLite Database
Pandas Library
Flask Framework

### Technical Implementation

- Structured design - Prevents data duplication
- API layer - Provides real-time access
- Data migration - Transforms spreadsheets to database format
- Query optimization - Sub-second response times
- Real-time updates - Instant data synchronization

# Future Development

Building on the database foundation.

1
System Deployment
Implement database system to replace current spreadsheets
2
Parent/Student Portal
Web access to real-time schedules
3
AI Scheduling Optimization
Intelligent schedule suggestions
4
Analytics Dashboard
Data-driven insights and reporting

### Implementation Timeline

- Month 1: Data migration and system setup
- Month 2: Portal development and staff training
- Month 3: Full implementation and optimization

# Conclusion

This project demonstrates how database systems can address school scheduling challenges by providing:

- Data consolidation from multiple spreadsheets into unified structure
- Efficient querying with sub-second response times
- Data integrity through automated validation
- Enhanced accessibility through mobile-friendly interfaces

The proposed relational database with API integration provides a foundation for future development while addressing current administrative requirements.

### Thank You

Questions about the database scheduling system?