Data Science Consulting

We offer advice in all areas of data science with the aim of empowering our customers to use this complex technology. Over more than 10 years, we have gathered experience with different data science technologies and tested these in various areas of application.

Our services: Turnkey or DIY?

Do you have your own data science team or want to build one? Or are you only interested in using this technology for a one-off project? In either case, our advisors will be happy to help: with training courses and knowledge transfer projects we can educate your employees or even provide you with turnkey and customised solutions directly.

Knowledge transfer projects

Our advisors are experienced trainers and can help you build in-house expertise in the area of data science.

Our advisors are experienced trainers and can help you build in-house expertise in the area of data science.

Knowledge transfer projects

In these knowledge transfer projects, supervised by us, you will build up the necessary competence for your experts to independently design data science solutions in the future.
The knowledge transfer projects are embedded in our program for establishing data science in companies: They build on our training courses and deepen this knowledge using a practical example in the context of your company. By successfully implementing your first projects, you will gain experience from real challenges and your employees will be ideally prepared for problems of a more complex nature.
The advisor learns about your company's internal processes during the knowledge transfer project and will be there to provide you with specific assistance and further suggestions via the Data Science Expert Support.

Turnkey solutions

We design customized solutions for your data science projects.

We design customized solutions for your data science projects.

Turnkey solutions

After the use cases have been identified, we implement your ideas in constant contact with end users and decision-makers. This way we ensure successful integration of the data science solution into your business processes.
We will take care of all the necessary steps for you: from data preparation and modelling and evaluation right through to deployment and maintenance. Depending on the problem at hand, greater benefit might be achieved with an application if it can access a larger data pool – which is why we pay particular attention to the future scalability and maintainability of infrastructure and software when designing your turnkey solution.

In order to be able to create elegant solutions even in the case of special challenges and prevent breakage of the tool chain, our development team supports us with project-specific developments.

In the beginning there was the use case...

Be it turnkey or DIY: at the beginning of each data science project you have to identify the use case. The more accurately it is described, the greater the chances are of the project being successful. The use case describes requirements and integrates organizational, technical and social aspects. For all those wishing to carry out a data science project, we have put together the Hitchhiker's Guide to a Data Science Use Case: A questionnaire that examines your use case from all angles. Fill out the questionnaire so that we can use our experience to advise you in an ideal manner. With the guide’s help, you can sharpen your intentions and get a more accurate idea of what questions you should expect during a data science project.

Competences

Get an overview of our areas of competence. We will support you in your data science project with best practices and proven standards.

Standards

In order to ensure a high quality of our advisory services, we base these on widely recognised standards.

In order to ensure a high quality of our advisory services, we base these on widely recognised standards.

Standards

In order to ensure a high quality of our advisory services, we base these on widely recognised standards and supplement these standards in line with our experience. For example, we have developed the Cross Industry Standard for Data Science Projects (CRISP-DM) into the Collaborative CRISP. Collaborative CRISP includes the important user acceptance monitoring as well as the use case identification at the beginning of every data science project. The standard gives guidance to data science novices in particular and provides points of reference for the project status.

Best Practices

Our best practices increase the efficiency with which data science projects are implemented.

Our best practices increase the efficiency with which data science projects are implemented.

Best Practices

We take great pleasure in constantly developing our best practices in our projects. During the projects, we gather experience and develop ideas based on this experience to optimize processes, save time and enable us to focus on what is essential: efficient solutions that exceed our customers’ expectations. With the support of our development team, we integrate our ideas into the programs used by us and enable other users to benefit from our experience in this way. Our software products contain several tools that make a clear project organisation and a simplified use of RapidMiner possible.