Consider an address attribute. Show that this can be modeled as a multi-level composite attribute where the component attributes include street, city, province, country and where street includes apartment number, street number, street name.

In the digital world, organizing and managing data is a critical task, and relational databases are one of the most efficient ways to handle this. A relational database is a collection of data items organized as a set of formally described tables from which data can be accessed or reassembled in different ways without having to reorganize the database tables.

The address attribute in the exercise is a classic example of how relational databases manage data by categorizing it into a structured format. In a relational database, each table represents a different entity, and each row within the table represents a record with a unique identifier known as a primary key. Each column would contain an attribute of the data.

In this case, an 'Address' table could have columns labeled 'Street', 'City', 'Province', and 'Country'. Further detail can be added by breaking down 'Street' into additional columns like 'Apartment Number', 'Street Number', and 'Street Name'. This sort of structure allows for easy access, querying, and manipulation of data, which is the foundation of efficient database management.

Diving deeper into the organization of data brings us to the concept of attribute hierarchy. This is a framework that represents the layers of complexity within a single composite attribute. Much like a family tree, an attribute hierarchy starts with a top-level category that branches out into more specific sub-categories.

Take our address example: at the top, we have the 'Address' as a composite attribute, and branching out from it are sub-attributes like 'Street', 'City', 'Province', and 'Country'. The hierarchy doesn't end there, as some of these sub-attributes can have their own sub-categories, such as the 'Street' being divided into 'Apartment Number', 'Street Number', and 'Street Name'.

This hierarchical organization aids users and database systems in understanding the relationships between different attributes, ensuring that data is retrieved in a contextual manner. It contributes to the normalization process in database development, helping to eliminate redundancy and optimizing the database's structure.

The process of creating a database structure that fits a company's needs is known as database modeling. This involves defining how data elements interrelate and designing the actual schema of the database. There are several models of databases, but relational modeling is by far the most common, especially for transactional databases.

During the database modeling stage, developers will utilize diagrams and flowcharts to make sense of complex attribute hierarchies and relationships. In our example model, a schematic tree diagram could illustrate how the 'Address' attribute is broken down into its components, outlining the structure in which data is stored.

Resembling an organizational chart, these diagrams help visualize the database's design, establishing how information is connected, how it can be accessed, and how it can be maintained efficiently. Effective database modeling ensures that the database is not only accurately reflecting the data but is also performing efficiently.