Data Science

Mit Data Science Wahrscheinlichkeiten prognostizieren.

Forecasting probabilities and recognising correlations with Data Science

We create competitive advantages for our clients by extracting knowledge from data

Our tasks include the processing, analysis and visualisation of your data. As a result, new insights and correlations can be gained. In addition, we develop predictions about important company key figures with the help of machine learning algorithms.

Our services in the field of Data Science:

Data Science aims to make predictions of activities, behaviour and trends using new and historical data . It involves the application of Big Data, statistical analysis techniques, analytical queries and automated machine learning algorithms to build predictive models.

Data management

Ensuring data quality, data availability and data transfer processes

Big Data Analytics and Data Engineering

Procurement, preparation and analysis of new and existing data

Model development

Development of mathematical models with statistical methods and machine learning

Model provision

Results are integrated into the decision-making process

Model monitoring

Monitoring performance to improve models at intervals


Documentation and visualisation of the results

Data science comprises various technologies with which data is cleaned, analysed and new information is obtained

Predictive Maintenance
Data Collection
Data Mining
Data Preparation
Data Visualization
Data Pipelines
ETL process
Application of Data Science
  • Information retrieval:
    The analysis of data from heterogeneous sources becomes possible with the support of Big Data techniques. Summarising the information provides new insights and supports strategic and operational decisions.

  • Discovery of similarity structures:
    Cluster analysis is used to identify groups that have similar structures from large data sets. No prior knowledge of the data is necessary, customers or products can simply be segmented.

  • Forecasting corporate key figures:
    The prediction of key figures through the application of forecasting models provides an insight into future developments. Thus, corporate decisions can be improved, and competitive advantages can be created.

  • Detection of dependencies:
    Exploratory data analysis uses statistical methods so that dependencies and correlations in the data are recognised and visualised. With the recognition of these correlations, the data can be better assessed and evaluated.

  • Automated data processes:
    The use of data pipelines facilitates the work with data by automating the collection, preparation and processing. The quality of the data has an enormous influence on the handling and use in the area of "Business Intelligence" and "Predictive Analytics".

Head of Data Science & AI

Your contactJian Wu

Head of Data Science & AI