Which two factors should be considered when determining the appropriateness of a dataset? (Choose two)

When evaluating the appropriateness of a dataset, the scale of data is a crucial factor because it influences how well the information represented aligns with the intended analysis or display requirements. Scale refers to the relationship between distance on the map and actual distance on the ground. If the scale is too large or too small for the analysis intended, important details may be omitted or misrepresented, impacting decision-making processes. For example, using a dataset with a very coarse resolution for a project that requires fine detail would likely lead to inaccuracies.

Choosing the scale in conjunction with another relevant factor helps ensure that the dataset can be effectively utilized for the specific context or geographic analysis. The geometry type, for instance, pertains to whether the data represents points, lines, or polygons, which can also significantly affect the appropriateness of the dataset based on how the data needs to be manipulated or visualized.

While display colors, geometry type, and feature class names may contribute to the usability and interpretation of a dataset, they do not fundamentally determine the data's appropriateness for analysis in the same way that scale and geometry type do.