What is a main characteristic of a logical data model?

A logical data model is primarily concerned with representing the structure of data in a way that emphasizes the logical relationships between different data entities, without delving into physical implementation specifics. One of its key characteristics is that it encompasses rules of normalization. Normalization is a critical process in data modeling that helps to organize data in a way that reduces redundancy and enhances data integrity. By applying normalization rules, a logical data model ensures that the data is accurately represented and that relationships between different data entities are clear and well-defined. This commitment to managing data integrity is foundational for effective database design and helps facilitate accurate and reliable data retrieval and analysis.

In contrast, ignoring rules of normalization would lead to a data model that is prone to redundancy and data anomalies, which are not desirable in a well-structured database. The assertion that the logical data model is only for relational databases underestimates its applicability, as logical data models can be utilized in various types of database management systems, not just relational ones. Lastly, focusing on physical storage details is characteristic of a physical data model rather than a logical one, which abstracts from those technical considerations to concentrate instead on the conceptual framework of the data.