Statistics
Statistics forms the methodological core of modern data science and analytics projects. It enables organizations to correctly interpret data, assess risks, generate forecasts, and uncover relationships that often remain hidden when using classical BI tools.
Whether in banking and insurance, manufacturing, logistics, or retail, statistical methods support business units in making more objective and well-founded decisions.
We provide services, training, and development support across relevant technologies – from open-source solutions such as R to Oracle R Enterprise and Minitab for engineering statistics. Our focus is on methodological rigor, transparent results, and practical implementation.
Services
Depending on the initial situation, priorities may include data quality, traceability, or technical implementation. The objective is to design analyses in a way that ensures reproducibility and seamless integration into existing processes – from initial data profiling to documented evaluation and operational handover.
- Prepare and describe data
- Visualize data and relationships
- Identify and document patterns
- Automate analyses and reporting
- Seminars and workshops
Benefits
Value is created when decisions are based on robust assumptions rather than intuition. Statistics makes uncertainty measurable, quantifies effects, and communicates results in a structured and comprehensible manner. Forecasts, tests, and models therefore become methodologically sound and clearly explainable to stakeholders.
- Broad spectrum of statistical methods and tools
- Support for open source, database integration, and engineering statistics
- Individual analyses, projects, and training
- Solutions for finance, manufacturing, logistics, and retail
- Integrated expertise in statistics, data science, and data engineering
Programming with R
R is a leading programming language for statistics and data science. It offers hundreds of packages for data analysis, visualization, machine learning, and reporting – making it well suited for exploratory analyses, complex models, and reproducible workflows.
Our Services
- Development of statistical models (regression, time series, clustering)
- Data cleansing, transformation, and exploratory data analysis (EDA)
- Reporting and dashboards using R Markdown and Shiny
- Integration into Microsoft Fabric, Power BI, and Oracle
Oracle R Enterprise
Oracle R Enterprise (ORE) combines the flexibility of R with the performance of the Oracle database. Statistical procedures are executed directly within the database – fully parallelized and without extensive data movement.
Our Services
- Modernization of existing ORE environments
- Development and deployment of ORE models
- Analysis of large datasets directly within the Oracle database
- Integration into PL/SQL processes and data warehouse workflows
Minitab
Minitab has been a standard tool in quality management and engineering statistics for decades. It provides a user-friendly interface for statistical testing procedures, process analysis, root cause analysis, and quality control. Typical application areas include manufacturing, production logistics, supply chain, pharmaceuticals, and medical technology.
Our Services
- Training and workshops on Minitab and engineering statistics
- Design of experiments (DOE)
- Process analysis and Six Sigma (Green/Black Belt support)
- Quality metrics (Cp, Cpk, SPC)
Frequently Asked Questions
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.
When is classical BI no longer sufficient and when do quantitative analyses become relevant?
Classical BI primarily focuses on descriptive reporting. Quantitative methods become relevant when relationships need to be modeled, hypotheses tested, or forecasts generated – for example using regression, time series analysis, or clustering.
What role does R play in data science and analytics projects?
R is an established programming language for statistical analysis and data science. It is well suited for exploratory analysis, complex modeling, reproducible reporting, and integration into existing BI and data platforms.
What is Oracle R Enterprise (ORE) and when is it used?
ORE enables the execution of statistical procedures directly within the Oracle database. This is particularly beneficial for large datasets, as analyses can be parallelized and performed without extensive data movement.
What is Minitab used for in engineering statistics?
Minitab is commonly used in quality assurance and manufacturing environments. Typical use cases include design of experiments (DOE), process capability analysis (Cp, Cpk), statistical process control (SPC), and Six Sigma initiatives.