Statistics with R
R is one of the leading programming languages for statistics, data analysis, and data science. It was designed specifically for scientific and analytical computing and provides a wide range of capabilities – from classical statistics to modern machine learning methods.
Organizations in banking, insurance, logistics, and retail use R to identify patterns, assess risk, and generate forecasts. Especially where statistical rigor and traceability matter, R stands out through package-based workflows and well-documented analyses – from exploratory data analysis to reproducible model execution.
Services
We support you in developing R scripts, statistical models, dashboards, and automated analysis processes – both as stand-alone solutions and integrated into platforms such as Microsoft Fabric, Power BI, RStudio, Oracle R Enterprise, or Shiny.
Results are typically delivered as traceable code, documented analyses, and reproducible reports. This enables analyses to be versioned, reused, and integrated into existing dataflows and reporting processes.
Statistical Analysis and Modeling
- Hypothesis testing, analysis of variance, regression models (linear, logistic, multivariate)
- Time series analysis (forecasting, seasonality, trends, ARIMA, Prophet)
- Segmentation, clustering, and exploratory data analysis (EDA)
- Machine learning models: random forests, gradient boosting, kNN, SVM
R Programming and Automation
- Development of reusable R pipelines
- Scripts for data cleansing, transformation, and quality checks
- Automated analytical workflows (batch scripts, scheduled jobs)
- Creation of reproducible reports (R Markdown, Shiny, PDF/HTML generation)
Reporting and Dashboards with R / Shiny
- Development of interactive dashboards in Shiny
- Web-based visualization of complex analytical results
- Combination of statistical models with intuitive user interfaces
- Hosting and deployment of Shiny applications
Integration into Existing Systems
- Embedding R in Microsoft Fabric (Spark plus R libraries)
- Integration of analytics in Oracle using Oracle R Enterprise (ORE)
- Use of R models in Power BI (R scripts, visuals)
- Combining R with Python, SQL, and data lakes
R in Microsoft Fabric
Even though Microsoft Fabric currently does not provide a native R kernel, R can be integrated via Spark and R packages through PySpark or SparkR:
- Execution of statistical models on large datasets
- Connectivity to lakehouse and data warehouse environments
- Combination of R methods with Python and Spark pipelines
- Provision of analytical models for Power BI
Especially relevant:
R visuals in Power BI enable the direct use of R within interactive dashboards.
R in Oracle (Oracle R Enterprise)
Oracle R Enterprise provides a powerful integration of R into the Oracle database. This makes it possible to execute statistical models directly within the database – without extracting data.
Benefits:
- Massively parallel in-database analytics
- Ability to work with large datasets without performance loss
- Native integration into PL/SQL processes
- Reproducible analytics for risk, forecasting, and data mining
We support both classical R with Oracle (R + ODBC/DBI) and Oracle R Enterprise.
Frequently Asked Questions on Statistics with R
This FAQ addresses the topics most frequently discussed in consulting engagements and training sessions. Each answer is concise and refers to additional material where appropriate. If your question is not listed, please feel free to contact us.
Which statistical methods can be implemented with R?
Typical methods include hypothesis tests, analysis of variance, and regression models, as well as time series analysis (e.g., ARIMA, Prophet), clustering, and exploratory data analysis (EDA).
How can analyses with R be automated and made reproducible?
Through reusable R pipelines, batch scripts, and scheduled jobs, as well as reproducible reports using R Markdown (PDF/HTML) and Shiny.
How can R be used in Power BI?
R can be embedded in Power BI using R scripts and R visuals to integrate statistical analyses directly into dashboards.
How does R work in Microsoft Fabric if there is no native R kernel?
R can be integrated via Spark, for example with SparkR or via PySpark while leveraging R libraries – including connectivity to lakehouse and data warehouse environments.
What is Oracle R Enterprise and when is it relevant?
Oracle R Enterprise enables in-database analytics: R models run directly within the Oracle database without extracting data, including parallel execution and PL/SQL integration.