What is the primary benefit of using a semantic model in data analysis?

The primary benefit of using a semantic model in data analysis is its ability to simplify complex queries. A semantic model provides a structured and intuitive representation of data, often using familiar terminology and relationships, which makes it easier for users to formulate their queries without needing to understand the intricate details of the underlying data structures.

By abstracting the complexities of the data storage and providing a higher-level view, users can focus on the data concepts rather than the technical implementation. This not only streamlines the querying process but also enhances the accessibility of data analysis for individuals who may not have deep technical skills. The semantic layer effectively acts as a bridge, allowing for more straightforward communication between the data and the user’s analytical tasks.

The options related to database size reduction, direct modification of the database, or the elimination of data cleaning do not fundamentally represent the core function of a semantic model. While those aspects can be important in other contexts, they are not the primary benefits tied specifically to the use of a semantic model in the realm of data analysis.