Uploaded May 2023 | Updated September 2026, 2 weeks ago
About the talk:
It's commonly known that R&Shiny can be used for quick prototyping, but what about quickly building complex production-ready dashboards? We will show that it’s also possible if only we initially invest some of our efforts into developing reusable production-ready dashboarding components. In our daily work, our team at Roche builds complex analytical dashboards for rapid Real-World-Data (RWD) exploration and hypothesis generation. Such dashboards need to work with different data sources and models, consist of different sets of integrated ready-to-use componentes, and have the ability to be customized with project-specific settings and modules. Because of those architectural drivers we propose and develop a modularized ecosystem of production-ready components, which are responsible for and very good at specific tasks, yet they are also properly abstracted so they can be easily reused in other projects and use cases. Some of the components that we’ve created are already open-sourced and we plan to open-source more of them in the future. In our talk we will show how one can build a production-ready dashboard using production-ready, well-tested components responsible for the following tasks: Generating rule-based artificial data for application development and testing. Creating complex cohorts using advanced filtering tools with clear separation of the interactive layer. Performing analysis on the selected cohort with an appropriate analytical module and visualizing the results. We will present those components, their features, benefits, and possible applications. What’s more we’ll show the effect of integrating those components in a single demo shiny app.
Speakers bio:
Kamil Wais is a contractor represented by 7N Consultancy Agency. At Roche he leads Real-World-Data Insights Engineering Team of R & Shiny developers. He is a Data Scientist, Scientific Software Engineer and a certified Agile Project Manager. He has PhD in History, as well as MSc in Sociology, and postgraduate degree in Statistical Methods in Business. Previously, he was a social researcher and academic teacher. He has a personal mission to help people to learn how to work with data to better understand the world and thus make better decisions.
Krystian is a Scientific Software Engineer at 7N. For many years involved in business consulting and analytical projects as well as conducting workshops in the R language. Currently focused on implementing complex Shiny components operating on real world medical data. He is interested in optimizing R-based workflows and pushing Shiny to the limit. Enthusiast of tea and vinyl records world.
About the talk:
It's commonly known that R&Shiny can be used for quick prototyping, but what about quickly building complex production-ready dashboards? We will show that it’s also possible if only we initially invest some of our efforts into developing reusable production-ready dashboarding components. In our daily work, our team at Roche builds complex analytical dashboards for rapid Real-World-Data (RWD) exploration and hypothesis generation. Such dashboards need to work with different data sources and models, consist of different sets of integrated ready-to-use componentes, and have the ability to be customized with project-specific settings and modules. Because of those architectural drivers we propose and develop a modularized ecosystem of production-ready components, which are responsible for and very good at specific tasks, yet they are also properly abstracted so they can be easily reused in other projects and use cases. Some of the components that we’ve created are already open-sourced and we plan to open-source more of them in the future. In our talk we will show how one can build a production-ready dashboard using production-ready, well-tested components responsible for the following tasks: Generating rule-based artificial data for application development and testing. Creating complex cohorts using advanced filtering tools with clear separation of the interactive layer. Performing analysis on the selected cohort with an appropriate analytical module and visualizing the results. We will present those components, their features, benefits, and possible applications. What’s more we’ll show the effect of integrating those components in a single demo shiny app.
Speakers bio:
Kamil Wais is a contractor represented by 7N Consultancy Agency. At Roche he leads Real-World-Data Insights Engineering Team of R & Shiny developers. He is a Data Scientist, Scientific Software Engineer and a certified Agile Project Manager. He has PhD in History, as well as MSc in Sociology, and postgraduate degree in Statistical Methods in Business. Previously, he was a social researcher and academic teacher. He has a personal mission to help people to learn how to work with data to better understand the world and thus make better decisions.
Krystian is a Scientific Software Engineer at 7N. For many years involved in business consulting and analytical projects as well as conducting workshops in the R language. Currently focused on implementing complex Shiny components operating on real world medical data. He is interested in optimizing R-based workflows and pushing Shiny to the limit. Enthusiast of tea and vinyl records world.
