For projects that use relatively little data, using a random forest algorithm will not give optimum results because it will unnecessarily subdivide your data. In these scenarios, you would use a decision tree, which will give you fast, straightforward interpretations of your data. But if you are working with a large dataset, random forest will give a more accurate, though less interpretable prediction.
