What type of modeling is used to visualize data relationships and user information needs?

Data modeling is a critical process used to visualize and define the relationships between various data elements and the information needs of users. This process involves the creation of abstract representations of data structures, allowing stakeholders to better understand how different data points interrelate and how they can be effectively utilized to meet specific business requirements.

Through data modeling, organizations can create conceptual, logical, and physical models of their data. These models help in laying the groundwork for database design and development, which is essential for creating efficient data management systems. By employing tools and methodologies of data modeling, such as Entity-Relationship Diagrams (ERDs), data flow diagrams, and UML diagrams, teams can visualize complex data relationships and clarify user requirements more effectively.

In contrast, while data access architecture pertains to how data can be accessed and utilized by applications, and a data dictionary provides information about data types and structures, neither directly focuses on visualizing relationships. OLAP is utilized for performing multidimensional analysis of business data, primarily for decision-making purposes, rather than for modeling the foundational relationships of that data. Thus, data modeling stands out as the appropriate choice for visualizing data relationships and user information needs.