This overview presents the structured phases of data mining in higher education, aiding self-study and understanding.
The poster provides a structured overview of the data mining process. It covers the six core phases: problem definition, data collection, data cleaning & preparation, exploratory data analysis (EDA), modelling & evaluation and deployment. The workflow is based on the CRISP-DM framework and adapted from established data mining techniques. It is intended for use in higher education and self-study contexts.
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Sarah Hörtnagel (2026) studied this question.
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