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?

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