Why Are Decision Trees So Popular in Data Analytics?

Decision Trees are popular in data analytics because they are easy to understand, visually intuitive, and work well for both classification and regression tasks. They handle numerical and categorical data, capture non-linear relationships, and require minimal data preprocessing. One major advantage is their transparency users can clearly see how decisions are made, which improves trust and interpretability. In the middle of any learning path, Data Analytics certification programs often highlight Decision Trees because they offer a perfect balance of accuracy and simplicity. They also scale well and form the foundation for powerful ensemble methods like Random Forests and XGBoost.