IT infrastructures for Data Science

To get the most out of data potential in times of digitalization, a seamless implementation of analytics solutions in your business processes is needed. The right infrastructure is the linchpin for the productive use of data science and AI in your company. For more than 10 years, our experienced solution and data engineers have been implementing IT infrastructures – from medium-sized businesses to international corporations. Get your infrastructure ready for the digital challenges of the future – with eoda.


„The implementation concept of eoda | analytic infrastructure consulting is very well elaborated and suits to our requirements perfectly. eoda has implemented a productive analysis environment for us that meets the strict requirements of a corporate IT environment without restricting the way data science works.“

Alex Burisch | IT Organizer| REWE International Dienstleistungs GmbH


Components for successful data science infrastructures

IT Infrastrukturen

IT infrastructures on premises and in the cloud

Infrastructures on premises or in the cloud with e.g. AWS and Microsoft Azure: We develop your “enterprise ready” infrastructure. What this includes: high availability, scalability, and load balancing to ensure the smooth functioning of your IT infrastructure. Even more: against the background of the security requirements, we guarantee a secure data connection for the operative operation of your analysis environment.

Operationalization of analytics

We provide you with an analytics platform that ranges from setting up the right IDE to hosting and scaling APIs.  Our system administrators and developers configure your servers, provide support and implement individual solutions for you. Through version management and deployment pipelines, we ensure that your data science projects are managed and deployed in a structured and highly automated manner. The implementation of the data science infrastructure can be handled and extended as dynamically as possible using infrastructure as code (IaC) tools.

data engineer hero

Data engineering

Where is data located? How can information be bundled? Where is data stored? Is it structured or unstructured data? With the help of the right data management strategy we pave the way for successful concepts in the field of data engineering. Data lake or data warehouse: we record your individual requirements and develop solutions for the professional use of data science in your company. A decisive aspect of this is the establishment of high-performance data pipelines as the center of your IT infrastructure.

Operation & support

With selected tools, release plans of the used components are monitored with a special focus on critical updates. In addition, server and software monitoring is a crucial part of a successful data science infrastructure.

Our toolset for your data science infrastructure

Your contact: Meltem Hekim

Portraitfoto Meltem Hekim