Reporting with R & Shiny

R is a widely used open-source programming language and statistical computing environment with extensive capabilities for demanding data science and data mining projects.

R and Shiny offer a distinctive combination of statistical power and flexible web development. With Shiny, interactive dashboards, analytical tools, and reporting portals can be built without traditional web programming. For organizations that already use R for statistical analysis or want to provide advanced analytical processes through an accessible interface, Shiny is a strong platform choice.

Shiny applications can be custom-designed, web-based, and deployed on local servers, in the cloud, or in container environments. This makes Shiny a lightweight, cost-effective, and highly flexible alternative to classic BI tools, especially for data- and model-intensive scenarios.

  • Statistical computing and data analysis: R provides a wide range of functions for statistical analyses such as regression models, ANOVA, and time series analysis.
  • Data visualization: It offers powerful libraries for building high-quality charts and graphics.
  • Open source: R is free and continuously developed by a large community, offering a broad ecosystem of extension packages.
RStudio interface with R code, data objects, and time series visualization in the plot window.

Reports

Hand-drawn bar chart – symbolizing reporting and data visualization.

Interactive dashboards and web applications

  • Dynamic visualizations with ggplot2, Plotly, highcharter
  • Interactive filters, tabs, tables, and forms
  • Real-time analysis, simulations, and scenario comparisons
  • Custom UI designs with Bootstrap themes or custom CSS layouts

Document and report generation

  • Generation of PDF, Word, or HTML reports via R Markdown
  • Automated reporting and scheduled report runs
  • Parameterized documents and repeatable analyses

Seamless integration of statistical models

  • Embedding regression models, ML algorithms, forecasting models, or clustering
  • Real-time calculations based on user inputs
  • Reproducibility and transparency in analytical decision-making

Technology

Multiple interlocking gears – symbolizing technical architecture and system logic.

Flexible data connectivity

  • Access to relational databases such as Oracle, SQL Server, PostgreSQL, etc.
  • Integration of REST APIs, CSV/Excel files, or cloud data sources
  • Use of R packages for data wrangling, machine learning, or text mining

Deployment options

  • Hosting via Shiny Server (open source or Pro)
  • Docker containers and Kubernetes deployments
  • Hosting in Azure or AWS cloud environments
  • Integration into Microsoft Fabric via Python/R notebooks or API interfaces

High flexibility

  • Fully customizable logic, layouts, and user interfaces
  • Ability to model organization-specific tools, calculation logic, or business processes
  • Open-source ecosystem with thousands of packages

Services

R provides an extensive statistical programming environment that can be used to run virtually any data science or data mining analysis.

Combined with RStudio Server and Shiny Server, analyses can be delivered through reports and made accessible to a broader audience.

Comeli dragon next to a large letter “R” – symbolizing r & shiny development.

Shiny app development

  • Development of tailored dashboard and analytics applications
  • User-friendly, clearly structured UI designs
  • Implementation of interactive visualizations and complex analytical functions
  • Creation of prototype or production-grade Shiny portals

Integration of statistical computing

  • Embedding statistical models (regression, machine learning, forecasting, time series)
  • Development of repeatable analytics pipelines with tidyverse, caret, tidymodels, or custom ML models
  • Validation of statistical models and result delivery in interactive dashboards

Automated reporting

  • Creation of PDF/Word/HTML documents using R Markdown and knitr
  • Parameterized reports and automated distribution
  • Development of comprehensive evaluation reports for business teams or audit bodies

System integration and data connectivity

  • Connectivity to SQL Server, Oracle, data warehouses, and cloud services
  • Building ETL/ELT processes with R or integrating into existing pipelines
  • Combined solutions with MS Fabric, Python, and Power BI

Deployment and operations

  • Setup of Shiny Server (open source or Pro)
  • Containerization (Docker, Kubernetes)
  • Role setup, authentication, and access concepts
  • Performance tuning, scaling, and monitoring

Training and coaching

  • Introduction to R Shiny for analysts and data scientists
  • Workshops for building professional Shiny dashboards
  • Best practices for UI/UX, performance, and code quality

References

Over the last 10 years, we have developed reporting systems with R for various industries and across different locations.

RStudio with statistical analysis and multiple charts in the output window.

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Questionnaire system with interactive question-and-answer visualizations and analysis functions for descriptive and inferential statistics. Development of charts.

Consulting firm, Munich

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Innovative question-and-answer visualizations in an electronic questionnaire

IT company, Berlin

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Analysis and reporting systems for machine and measurement data in production

Manufacturer, Stuttgart

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Combination of current data and the use of forecasting models for extrapolation

Bank, Cologne