Understand conceptual data modelling, entities, attributes and relationships, entity relationship (ER) diagrams, and the degrees of relationship (one-to-one, one-to-many, many-to-many).

The relationship between Student and Course is many-to-many (M:N): a student takes many courses and a course has many students.

It cannot be implemented directly because a relational table can hold only single (atomic) values in each field, so neither table can store an unbounded list of the related records from the other side without repeating data.

It is resolved by introducing a linking (junction) entity, for example Enrolment, placed between Student and Course. Enrolment holds a foreign key to Student and a foreign key to Course (often together forming its composite key), turning the single many-to-many relationship into two one-to-many relationships: one Student has many Enrolments, and one Course has many Enrolments.

Markers reward identifying the M:N degree, the reason it cannot be stored directly, and resolving it with a linking entity that creates two one-to-many relationships.

Producing a conceptual data model involves identifying the entities the system stores data about, the attributes that describe each entity, the relationships between entities and their degree, and choosing a primary key for each entity, all independently of any particular software.

An entity is a real-world thing the database stores data about, for example Customer. An attribute is a property of an entity, for example a Customer's Name or Address. A relationship is a link between entities, for example a Customer places an Order, which is a one-to-many relationship because one customer can place many orders.

Markers reward the modelling steps (entities, attributes, relationships, keys) and a correct distinction between entity, attribute and relationship with a coherent example.