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Data Science

Data analysis

Analyses turn data into insights and knowledge. This creates a sound basis for decision-making from questions or ideas. In this way, it is possible to manage organizations proactively and sustainably without leaving too much to chance. Profitable data analysis also means reducing complexity and thus eliminating potential sources of human error.

Data analysis for better decision making

Relying purely on experience often carries the risk of relying on approaches that are no longer appropriate for the organization's current situation or environment. In contrast, carrying out methodically robust analyses enables the meaningful supplementation of entrepreneurial intuition in order to make decisions in the best possible way.

Through data analysis, it is possible to evaluate decisions and measures taken as well as to adjust, expand or reverse them if the goal is not met. 

01 Descriptive Analysis

Present data summarized in key figures, describe and create a basis for understanding

02 Explorative Analysis

Searching for patterns and structures, uncovering new questions and possibilities to make "Big Data" usable

03 Inferential Statistics

Using sampling to establish relationships and differences for gaining knowledge

04 Qualitative Analyse

Generate insights from data that are not available as numbers, such as texts, interviews, etc.

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