Which step comes directly after data transformation in the data mining process?

In the data mining process, data transformation is crucial as it prepares the data for analysis by converting it into a suitable format. Once the data is transformed, the next step is to apply data mining techniques to discover patterns or relationships within the data. This step involves using algorithms to identify insights, trends, and anomalies, which can inform decision-making.

Data mining is focused on extracting meaningful information from the transformed data, making it the immediate subsequent step. After successfully applying data mining techniques, the results can then be evaluated and represented as knowledge, leading to informed conclusions and recommendations.

Understanding the sequence of these steps helps highlight the continuous flow of the data mining process, where each phase builds on the previous one to lead to actionable insights.