Withdrawn - 11. "From Local to Live: Taking Analyses into Production"

In many research applications, analyses are generated through local scripts or notebooks, often built for one-time use and confined to a single machine. While effective in the short term, these workflows limit reproducibility, collaboration, and broader scientific impact. In this poster, I address the importance of transitioning these isolated efforts into robust, shareable tools. I explore the benefits of deploying reusable, open-source, and publicly accessible software, and highlight how productionizing analysis workflows enhances reproducibility, fosters collaboration, and enables researchers to build on each other's work more efficiently. Drawing from the experience within the Statistical Engineering Division of the National Institute of Technology, I present a practical overview of the systems, practices, and infrastructure that I use to take local code into production. This includes containerization, API development, continuous integration, and cloud deployment strategies that support sustainable, scalable research software. By showcasing real-world examples, I hope to inspire other teams to consider the lifecycle of their analytical work, from isolated, often scattered workflows, to living, maintained software that can support ongoing and future research.

software

deployment

research and development

computing systems 

Mid-Level

Knowledge

Women in Statistics and Data Science 2025