Which process could lead to a simplified understanding of data relationships?

Normalization is a database design technique that organizes data to reduce redundancy and improve data integrity. By systematically structuring the tables and columns in a database, normalization helps clarify the relationships between different sets of data. It achieves this by dividing larger tables into smaller, related tables, each focusing on a specific subject. This process ensures that each piece of data is stored in one place, which simplifies understanding how entities relate to each other.

When normalization is applied correctly, it results in a clear schema that reflects logical relationships, making it easier for users to query the data effectively and retrieve accurate results. It assists in maintaining data consistency, as updates, deletions, or insertions can be performed without the risk of creating anomalies.

In contrast, denormalization involves intentionally introducing redundancy to improve query performance, which can create complexities in understanding data relationships as multiple copies of the same data exist across the database. Data migration refers to the process of transferring data from one location to another, which does not inherently clarify data relationships. Data aggregation involves summarizing detailed data into a more compact form, which may obscure the underlying relationships rather than simplify them.