video1.0<iframe src="https://www.loom.com/embed/131343d637ce43feb03cafe3ed0d693b" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/131343d637ce43feb03cafe3ed0d693b-010507ca4f72af45.gif294.439In today's video, I walk you through our automated third gender diversity profiler workflow. We process user information for up to 500 users, but we limit it to 50 at a time, looping through the data to determine gender based on names from another website. The results show that we have 400 female and 100 male authors, which we visualize in a pie chart for easy interpretation. I encourage you to review the output and think about how we can further utilize this data to enhance our diversity initiatives.