Success Stories

On difficult computer science problems we are in our element. Combining research and practical aspects requires a deep understanding of the mathematics and computer science backgrounds, comprehensive knowledge about the current state of research and technology, as well as long-term experience in practical and interdisciplinary application.

Story #1

Chemistry (DAX)

Data Strategy /
Roadmap /

Modern companies hold an enormous amount of data from various sources, in various formats and in various levels of quality. In order to make this data useful for applications in research and development, we support a company in the chemistry sector with conception and implementation of a Hadoop-based data lake as well as diverse data science applications on that data lake. Mondata acted as architecture lead on parts of this project. On top of that, we were involved in the conception and realization of Spark-based applications for the evaluation of data on the data lake.

Story #2

Automotive (DAX)

Roadmap /

Big data and data science have the potential to substantially optimize business processes. The prerequisite for this is the availability of recent data and the ability to evaluate them in a reasonably efficient way. Working with a company in the automotive industry, we have been responsible for the conception and realization of a data lake used for after-sales data. In addition to planning the architecture, we developed an ingest route for online processing of streaming data and implemented evaluation methods and real time dashboards with substantial use for management of the company.

Story #3

Pharmaceutics (Mid Tier)


The development of new agents is one of the most challenging and most important tasks in life science research. Pharmaceutical companies make use of the most cutting-edge informatics and bioinformatics methodology to support their design process. We have extensive experience in the conception and realization of mordern algorithms and data science methods for the simulation and statistical prediction of relevant chemical properties. This also includes the development of databases and frontend applications.