Suppose a company that sells products has a product entity type with the following attributes: prodNum, prodDesc, prodPrice. Suppose all three attributes are single-valued and that prodNum is a key attribute - each product has a different product number. Illustrate this information in an ERD.

In database design, creating an Entity-Relationship Diagram (ERD) helps in visualizing the structure of the database. An ERD consists of entities which represent data or objects, such as 'Product', and the details about those entities are described by attributes.

Attributes in an ERD are depicted as ovals connected to their entity with lines and can be either single-valued or multi-valued. Single-valued attributes, as the name suggests, hold a single value for an entity instance. For instance, the 'prodDesc' (product description) is single-valued as each product has only one description. On the other hand, multi-valued attributes, which are not depicted in this exercise, can hold multiple values for an entity instance. Using attributes effectively in ERDs represents the nuances and details of data storage and retrieval in a clear, concise way, which is crucial for database accuracy and efficiency.

When designing an ERD, it's essential to include all attributes that define an entity, ensuring that the data models reflect real-world scenarios as closely as possible. This precision in detailing attributes leads to more robust and reliable databases.

In the context of ERDs, a key attribute plays a critical role in distinguishing each entity instance uniquely. Key attributes are underlined in an ERD to signify their importance. For example, in a company's product database, 'prodNum' (product number) could be a key attribute as it uniquely identifies each product in the database.

No two entities can have the same value for a key attribute which ensures that each record is uniquely identifiable. This is analogous to how a Social Security Number identifies an individual uniquely in a national database. Ensuring that key attributes are properly defined is imperative as they are foundational to the relational integrity and query functionality of a database. Mistakes in key attribute selection can lead to duplication and data inconsistency, undermining the database's purpose.

Database design is a critical process that involves defining a database's structure to ensure it meets the necessary requirements and supports operations such as queries, updates, and management of the data. Effective database design follows a series of steps, beginning with requirements gathering and ending with implementation and maintenance.

Using ERDs is a part of the logical design phase, where entities and relationships between them are mapped out. Clear communication about design specifications, such as identifying key attributes like 'prodNum' or understanding the nature of attributes, is crucial. A well-designed database minimizes redundancy and promotes data integrity, which improves performance and user trust in the system. Moreover, by scaling effectively with the addition of new data or changes in requirements, a well-designed database proves to be a robust part of any application's infrastructure.