Why is it beneficial to combine feature classes into one larger feature class?

Combining feature classes into one larger feature class is beneficial primarily because it helps decrease data redundancy and enhance organization. When multiple feature classes are merged, there is a reduction in overlapping data and potential duplication, which streamlines data management. This consolidation contributes to a more organized dataset, making it easier for users to access, edit, and query the data, which is particularly important in complex projects with multiple data contributors.

By having fewer feature classes, it simplifies the data structure and can improve the performance of geospatial queries or analysis tasks. Moreover, it allows for a more coherent data model where related features are housed together, improving the integrity and consistency of the dataset. Overall, merging feature classes leads to more efficient data handling and facilitates easier maintenance and updates.