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IT SupportKatanga Business MeetingApr to May 2026

Katanga Business Meeting 2026

I supported attendees on Brella and automated badge-data preparation for a three-day business forum.

Katanga Business Meeting 2026 event banner

Selected outcomes

  1. Approximately 1,150 attendee records processed
  2. Roughly 300 to 350 badges printed on site
  3. Ticket types mapped to badge access levels
  4. Manual full-dataset reconciliation replaced

What I did at KBM

Katanga Business Meeting brings companies, entrepreneurs, and decision-makers together around regional business opportunities. For its 2026 edition, participants used Brella to access the event, connect with other attendees through its matchmaking tools, and create virtual exhibitor stands.

I joined the project through as IT Support, reporting to Candy Mujinga Willems. From April through the end of May, I helped attendees use Brella, set up exhibitor stands, and use its matchmaking features. I also printed access badges on site from 20 to 22 May.

The badges had different access levels based on ticket type. A mistake in the attendee data could therefore give somebody the wrong badge.

Automating the badge list

At first, the team exported the full Brella dataset and compared it with the badge file by hand. They had to find every new or changed attendee before updating the badge macro. Registrations kept changing, so they had to repeat the same work.

I built a Python script that retrieved participant records through Brella’s official REST API and exported badge-ready data to CSV. The integration used each participant’s Brella user ID to detect records already processed. It also read the ticket-type field and applied conditional rules to produce the corresponding badge access level.

Handling incomplete data

Some attendee records were incomplete. The script reported them so I could fix them manually. It retried some API errors automatically and reported the others. If it found an unknown ticket value, it used a default access type and flagged the record for review.

Three days on site

During the event, I printed roughly 300 to 350 badges and handled access issues as they came up. I could see immediately whether the data produced by the script worked with the badge macro and the printers.

We did not measure the exact time saved. What changed was the process. The team no longer had to compare the full dataset by hand each time registrations changed.