Sample: In this step, a large dataset is extracted and a sample that represents the full data is taken out. Sampling will reduce the computational costs and processing time.
Explore: The data is explored for any outlier and anomalies for a better understanding of the data. The data is visually checked to find out the trends and groupings.
Modify: In this step, manipulation of data such as grouping, and subgrouping is done by keeping in focus the model to be built.
Model: Based on the explorations and modifications, the models that explain the patterns in data are constructed.
Assess: The usefulness and reliability of the constructed model are assessed in this step. Testing of the model against real data is done here.
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