Our Services

Find the right offer for your needs here

Support with statistical analyses for your thesis, papers, research projects and scientific studies.

Data-driven insights for companies - from market analyses to process optimization.


Support for Bachelor, Master and PhD theses.
Help with understanding software such as SPSS, R, Excel etc.
Step-by-step explanation of statistical concepts and methods.

Performing linear regressions, factor analysis, t-tests, ANOVA and other statistical procedures.
Cleaning, transformation and modeling of data for scientific studies.
Support with the interpretation and graphical representation of results.

Development of a solid research design for experiments, surveys or quantitative studies.
Support with the operationalization of variables and selection of suitable measurement instruments.
Consultation on data validity, reliability and sample size (power analysis).

Help with the structured presentation of results in scientific papers..
Support with the writing of statistical reports, abstracts and method sections.
Creating high-quality visualizations (graphs, tables) for publications..


Structured analysis of company data to identify trends, risks and optimization potential.
Development of statistical models and predictions to support data-driven business decisions.
Application of machine learning, regression analyses and probability calculationsto create precise forecasts.

Developing interactive dashboards in Power BI, Tableau, R or Pythonto make complex data understandable.
Creating automated reports and management visualizations for data-based decision-making processes.
Optimization of existing reporting structures for efficient communication of KPIs.

Identification of customer segments, behavioral patterns and market trends through data-based analyses.
Optimization of marketing strategies through A/B testing and data-driven target group analyses.

Development and optimization of SQL databases and data pipelines for efficient workflows.
Data cleansing, processing and integration to improve data quality.
Implementation of automated data processingto reduce manual tasks.

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