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Attandance Tracking from Microsoft Teams Report

Summary

Automated Microsoft Teams attendance tracking by normalizing participant names and applying fuzzy matching to accurately sync attendance data with an official database via a Streamlit web application.

Problem

Attendance tracking from Microsoft Teams is often done manually by matching attendance reports with a participant database.

Key challenges:

  • Inconsistent participant names
    • Abbreviated names
    • First name–last name only
    • Extra labels such as (Unverified), (External), (guest)
    • Variations in capitalization, punctuation, and formatting
  • Large scale usage
    • Applied across 10+ classes
    • Multiple sessions with dozens of participants
  • Manual process is time-consuming
    • High risk of human error
    • Difficult to audit and maintain consistency

As a result, attendance tracking becomes an operational bottleneck that consumes significant time and effort.

Solution

Built an Attendance Synchronization & Matching System using Python that:

  • Ingests Microsoft Teams attendance reports
  • Performs name preprocessing and normalization
  • Matches participants against an official database using fuzzy string matching
  • Automatically generates attendance summaries (present/absent and statistics)

Workflow:

  1. Upload Participant Database
  2. Upload Microsoft Teams Attendance Report
  3. The system automatically:
    • Cleans and standardizes participant names
    • Applies fuzzy matching with a configurable threshold
    • Determines attendance status
    • Aggregates attendance data across sessions
  4. Outputs are ready to use with no manual intervention

The solution is deployed as a Streamlit web application, making it accessible to non-technical users.

Impact

  • ⏱️ Significant time savings
    • Manual work reduced from hours to seconds
  • 📉 Reduced human error
    • Consistent and standardized name matching
  • 📊 Clean and structured attendance data
    • Easier analysis, reporting, and auditing
  • 🚀 Scalable
    • Can be reused across multiple classes without workflow changes
  • 💼 Business-ready
    • Suitable for Edu-Tech, training programs, and stakeholder reporting

Tech Stack

  • Python
  • Pandas – data processing and aggregation
  • RapidFuzz – fuzzy string matching
  • Regex (re) – text preprocessing and normalization
  • Streamlit – interactive web application
  • Microsoft Teams Attendance Report – data source

Extras (Optional)

  • Configurable fuzzy matching threshold to adapt to data quality
  • Modular code structure for easy extension
  • Future enhancements:
    • CSV / Excel export
    • Analytics dashboard
    • Direct database or LMS integration
    • Automated attendance reporting