The initial situation
Your data lies around unused
Huge amounts of data are kept in every company. As a rule, they are highly complex and diverse. The necessary resources and expertise to tap them are not available. Despite investing in their own data science solutions, many companies do not even begin to realize the potential added value that could be extracted from them.
UMB Data Science Service
The challenges
- Data is stored in isolation
Data stored in isolation is difficult to use and integrate due to its separation from other data sources. This can lead to data inconsistencies and thus affect the quality of the data. It can restrict access by authorized users and therefore impair the efficiency of business processes.
- Lack of understanding of the potential of this data
Data volumes represent both an enormous challenge and a huge potential. However, the implementation of proprietary data science solutions often leads to a complication of everyday business life.
- Data pipelines are not target-oriented
Non-targeted data pipelines lead to large amounts of unstructured data from different sources. This data can have different formats, qualities, and structures, making integration and data cleansing difficult.
Data Science
is a big buzzword jungle; hardly anyone has a real understanding of it.
The solution
The UMB data scientist
turns your data _into valuable knowledge
The data scientist works in three steps. First, the current status is evaluated. Then, existing solutions are cleaned up and improved. Finally, he implements goal-oriented visualizations and applications. Through this process, insights will be derived from the raw data, which will help to optimize business processes and gain a competitive advantage.


Your Advantages
Evaluation of your range of options
Solutions based on data _not opinions
24/7 support and operations
Solutions on AWS, GCP, Azure and Onsite
Consulting, security, and engineering from a single source
Save time with a data scientist
Enterprise
40,000 hours/year
SME
10 000 hours/year
Creating time with a data scientist in digitization
With the same budget 30 colleagues more for your core business
40 000 h/year
*1 360 working hours per year
Your contacts
