We help to salvage the treasures hidden in your data.
Every job is unique. We bring the required flexibility and creativity to be able to solve a variety of different tasks.
We combine classical methods with state-of-the-art technologies like artificial intelligence for insightful analyses.
Years of international experience enable us to realistically assess projects and deliver results in due time.
Our offer in a nutshell: DSaaS — Data Science as a Service
RAWS Consulting offers various operations in the area of data science as tailor-made, modular services for companies. This gives you straightforward and professional access to these crucial skills.
Starting from your raw data, we deliver a complete package, where not only insightful results but also their communication and data privacy are put to the forefront.
We attach great importance to individuality, given that in our field of consulting every job is unique.
Along with consultation custom-made for your requirements we provide all services bilingually (German / English), so that you can for example get a German documentation at no extra charge.
We can look back on many years of international experience in the evaluation and analysis of data.
For that purpose we not only work with classical methods of statistics, but also with state-of-the-art technologies like artificial intelligence.
The fundamental orientation of our services permits a maximum of flexibility, such that there are almost no limits to our field of application.
Typical applications are business analytics, process optimization, the analysis and prediction of customer behaviour and many more.
All our applications, however, pursue a common goal: To generate the maximally possible additional value from your data, so that you are one step ahead of your competitors due to our insightful analyses and predictions.
You are wondering if or how we could potentially be contributing to your project? Get in touch for a non-binding assessment at no charge.
Our projects comprise a variety of tasks in the field of data science. The core component are analyses, the results of which we try to integrate into existing structures as well as possible.
The exploratory analysis aims for identifying previously unknown correlation in available data. This is an important cornerstone of every project to get an idea of possible parameters, their impact and their importance. We typically use classical methods of statistics for this step.
The predictive analysis is based on the exploratory analysis and is supposed to predict future events by means of a mathematical model. For this kind of analysis we deploy both classical methods of statistics and state-of-the-art technology like artificial intelligence, depending on the particular project.
A thorough integration into the existing environment is essential to ensure a sustainable benefit stemming from our results. For this purpose we provide e.g. container virtualization and consulting in the area of CI/CD pipelines, such that you can profit from our results without limitations.
We deliver our results as custom-made packages. You not only determine the due date and the form of delivery, but also the individual extent. You can e.g. get a thoroughly documented source code or a separate documentation, but also a final presentation or a workshop is possible.
The raw data collected in many places often disguises that a significant additional value can be obtained from them. Instead of archiving or deleten this data we help you to discover and utilize such potential.
By using our services you not only profit from our expertise but also retain a maximum of agility. You define the extent of our collaboration, where no extraordinary expenditures or preparations are required.
Based on the results of our analyses you can derive e.g. new product ideas or directions of development. You thereby ensure a sustainable benefit from our services, even after our collaboration ended.
After establishing a first contact we would be happy to pay you a visit to find out more about your case and to see our potential contributions.