cross-industry-anomaly-detection-solutions.md

talk_id	talk_slug	talk_type	talk_tags	session_slug	talk_title	talk_title_short	talk_materials_url	speakers
22191	cross-industry-anomaly-detection-solutions	regular	access modeling shiny	working-with-people	Cross-Industry Anomaly Detection Solutions with R and Shiny	Cross-Industry Anomaly Detection Solutions with R and Shiny		name affiliation url username photo bio Tanya Cashorali TCB Analytics webpage twitter github linkedin affiliation http://www.tcbanalytics.com https://twitter.com/tanyacash21 https://github.com/tcash21 https://www.linkedin.com/in/tanyacashorali/ http://www.tcbanalytics.com tanya215 /assets/img/2022Conf/_talks/22191_tanya-cashorali.jpg Tanya Cashorali is the founder of TCB Analytics, a boutique data and analytics consultancy. She hosts a world-wide community network of over 500 data enthusiasts, has helped universities launch data science programs, and is a frequent speaker at tech conferences.

This session highlights two anomaly detection use cases in production: identification of problematic life sciences manufacturing units and identification of significant newsworthy events. With both solutions, Shiny is integrated with live data to provide early detection for proactive intervention. Shiny’s intuitive user interface also allows for interaction with the data behind anomalies to uncover potential causes and paths to action or resolution.

The session also briefly highlights a rapid prototyping development approach with Shiny. This technique allows for collaborative refinement of the underlying anomaly detection model in R, quickly incorporating user feedback, where end users may not have in-depth machine learning knowledge.