This document discusses the data analytics process from data preparation to model deployment. It describes how data is partitioned into training, validation, and test sets. It also outlines the typical steps in data preparation, model training and optimization, and deployment. Examples of classification problems and datasets are provided to illustrate applying this process. The document promotes resources from KNIME for learning and connecting with the community.