Your Guide to Quality Data Science Products

Follow each step as I develop a form with Shiny and Behavior-Driven Development. Learn practical techniques for better software design through automated tests. Testing your Shiny applications shouldn’t be an afterthought. Many developers write tests after building features, missing the core benefit of test-first development: tests as design tools. I’ll walk you through how I built a small content submission form using Behavior-Driven Development (BDD), starting from absolutely nothing. Whether you’re building a new app or adding a feature, the steps are the same. Follow along and see how tests drive design decisions, keep business value visible, and make refactoring safe.

Learn how to write reliable R tests by wrapping external dependencies and using `testthat::local_mocked_bindings`. Make your tests fast, clean, and predictable.

How to speed up clinical trials since you don't have to wait months for clinical trial data to become actionable insights.

How R & Shiny are transforming clinical trial analytics and why your company can't afford to wait four months for clinical trial data to become actionable insights

Learn why traditional analytics approaches can't handle today's complex data ecosystem and what opportunities exist to dramatically accelerate your decision timeline.

Try Rhino 1.11.0 with auto test reruns and devmode for a smoother R development setup.

Shiny, React, or Python? Learn how to choose the right stack for building and scaling decision support systems.

Practical tips for combining {renv} and Bioconductor to manage dependencies and ensure reliable analysis outcomes.

Learn how good automated testing enhances GxP-compliant software delivery with better quality, scalability, and reliability.

Want to learn time series forecasting in R with machine learning models? Read our guide and predict the future with linear regression.

Optimize your R Shiny app with advanced caching strategies for faster response times and improved user experience.

Discover how to use the pointblank R package for effective data validation in R Shiny applications. Learn key workflows, examples, and best practices to ensure data integrity.