Dimensionality refers to the number of independent directions or axes in a space. In everyday life, we experience three dimensions: length, width, and height. Each dimension adds complexity and allows for the representation of objects in a more detailed manner. For example, a cube has three dimensions, while a point has zero dimensions, and a line has one dimension. In mathematics and data science, dimensionality can also describe the number of features or variables in a dataset. High-dimensional data can be challenging to analyze due to the "curse of dimensionality," which makes it harder to visualize and interpret relationships. Techniques like dimensionality reduction help simplify complex datasets while retaining essential information.