r-markdown-rstudio-connect-r.md

talk_id	talk_slug	talk_type	talk_tags	session_slug	talk_title	talk_title_short	talk_materials_url	speakers
22221	r-markdown-rstudio-connect-r	regular	communication pro-products process	data-quality	R Markdown + RStudio Connect + R Shiny: A Recipe for Automated Data Processing, Error Logging, and Process Monitoring	R Markdown + RStudio Connect + R Shiny		name affiliation url username photo bio Kolbi Parrish California Dept. Public Health & UCSF webpage twitter github linkedin affiliation kolbi_parrish /assets/img/2022Conf/_talks/22221_kolbi-parrish.jpg Kolbi Parrish is an Informatics Specialist working at the California Department of Public Health (CDPH) through the University of California, San Francisco. She has worked in public health for over 10 years, has a Master’s degree in Industrial and Organizational Psychology, and is interested in leveraging data and technology to further public health goals. name affiliation url username photo bio Andy Pham UCSF & CA Dept. Public Health webpage twitter github linkedin affiliation https://github.com/PoppinHandy https://www.linkedin.com/in/handy94/ andy_pham /assets/img/2022Conf/_talks/22221_andy-pham.jpg Andy is a clinical informatics specialist working at the California Department of Public Health Data Processing and Informatics section, where he works on building disease surveillance data pipelines for gathering, processing and reporting. Andy has a Master's in Health Informatics and has been an avid R user since 2017.

R is more than just a tool for data analysis– it can help streamline and automate processes, including managing and monitoring data pipelines. This presentation highlights how R Markdown, RStudio Connect, and R Shiny can be utilized to automate data processing, error logging, and process monitoring. By the end of the presentation, attendees will better understand: (1) how RStudio Connect paired with R Markdown can be used to automate data processing, (2) that packages such as blastula and loggit can be used within R Markdown documents scheduled on RStudio Connect to email users when an error is encountered during data processing and log those errors, and (3) that the resulting logs can be fed to a Shiny app to enhance process monitoring.