Data assessment day
Not sure about which of your data assets are valuable? Wondering how to put the available data to good use?
Then the data assessment day is a good starting point! We come to meet you on site and help you to make an initial assessment:
- What is practical in your situation?
- What is fundamentally possible?
- What can be advantageous for you?
The data assessment day does not require extensive preparation or investment. So, you can take it slow and approach the topic of data use at your own pace.
Data usage consulting
Already know what your data capital is, but are still unsure about which specific utilisation strategies to choose?
We will be glad to help you assess the feasibility of different approaches and the benefits that can be achieved with them. We will support you in planning realistic milestones as well as in the concrete conception.
You have an existing data capital.
Tasks of a Data Science Project
We are often asked what such a project requires. There is no universal answer to this question. However, the following diagram shows the areas of responsibility that may be relevant to a data science project. This will give you a good idea of the interdisciplinary work we do at our institute on a daily basis.
Colleges and universities of applied sciences are also increasingly using the possibilities offered by data science to assess the needs of student cohorts. The possibilities offered by data science lead to concrete management options in the core business. One of the most common application groups is the prediction of dropouts and the countermeasures initiated in an automated or semi-automated manner.
Companies often use data science for similar purposes. Here, it is often a question of minimising the churn rate or identifying reasons for customer churn. The corresponding findings are used to "win back" the customers in time.
By means of a customer segment analysis, companies can use existing data to discover new insights and sales potential. Data science goes well beyond the traditional techniques of market research. Of course, these techniques (such as factor analysis or conjoint analysis) can also be used in the context of a data science project. As a rule, however, we go beyond these techniques.