Converting ER Diagrams to Tables Flashcards
Why is it not a simple one-to-one translation from an ER diagram (conceptual schema) to a relational table (relational schema)?
The translation from an ER (Entity-Relationship) diagram to a relational schema is not a simple one-to-one process because not all ER constructs can be directly translated into relational structures. The complexity arises due to differences in the representation of relationships, cardinality, and other concepts between the two models.
What are the primary goals of restructuring ER diagrams before translation into a relational schema?
The primary goals of restructuring ER diagrams before translation into a relational schema are to reduce redundancy and improve efficiency. This involves refining the conceptual schema to eliminate ambiguities, represent relationships clearly, and ensure that the resulting relational schema is well-organized and efficient.
What are the typical steps involved in the process of translating ER diagrams into relational schemas?
The typical steps in translating ER diagrams into relational schemas include:
Restructure ER Diagrams: Refine the ER diagram, resolve any ambiguities, and ensure clarity in representing entities, relationships, and attributes.
Translation into Relational Schema: Map entities, relationships, and attributes from the ER diagram to tables, keys, and constraints in a relational database schema. This involves creating tables, defining primary and foreign keys, and establishing relationships.
What is the recommended approach for handling multi-value attributes in an entity within a relational database design?
Ideally, multi-value attributes should be removed from the entity and split into a separate relation, especially when aiming for normalization and a more structured database design. This involves creating a new table (relation) to represent the multi-valued attributes and establishing a relationship between the original entity and the new relation.
Why is it beneficial to split multi-value attributes into a separate relation and a weak entity?
Splitting multi-value attributes into a separate relation and a weak entity is beneficial for several reasons:
Normalization: It supports the normalization process, reducing redundancy and improving the overall structure of the database.
Maintainability: It enhances the maintainability of the database by organizing data more systematically.
Flexibility: It allows for a more flexible and extensible design, making it easier to adapt to changes in requirements.
What is the role of the new relation when handling multi-value attributes?
The new relation represents the multi-value attributes and establishes a relationship with the original entity. This relationship typically involves using foreign keys to link the instances of the original entity to the corresponding instances in the new relation.
How can a weak entity be defined in the context of a relational database?
A weak entity is an entity that depends on the existence of another entity. Unlike regular entities, weak entities often do not have a candidate key of their own and rely on the primary key of a related parent entity.
What is a common characteristic of the primary key for a weak entity?
The primary key for a weak entity is typically derived from the primary key of its parent entity. It uses the primary key of the parent entity as part of its own key to establish a dependency.
What are some common reasons for the existence of weak entities?
Weak entities usually result from conscious choices by data modelers or when there is no global authority capable of creating a unique identifier. They are designed to represent entities that cannot exist independently and are inherently tied to the existence of another entity.
How should one approach handling repeating groups in an entity within a relational database design?
When dealing with repeating groups in an entity, it’s essential to be cautious as these multi-value attributes may be logically related. For instance, considering a scenario where, on each visit, a patient sees one doctor per day and only consults one doctor about one symptom, assumptions like these should be carefully considered.
What are potential issues with repeating groups, and how can they be addressed?
Potential issues with repeating groups include redundancy and difficulty in maintaining data integrity. To address these issues, it’s advisable to create separate entities and relationships. In the example given, creating a Doctor entity and establishing relationships based on assumptions can lead to a more structured and normalized database design.
Why might it be beneficial to create a separate entity (e.g., Doctor) and establish more relationships in the case of repeating groups?
Creating a separate entity, such as a Doctor entity, and establishing more relationships allows for a more flexible and normalized database design. It helps avoid redundancy and ensures that relationships between entities are well-defined, making it easier to query and maintain the database.
What conditions should an entity satisfy in a relational database model?
An entity in a relational database model should satisfy at least one of the following conditions:
It has at least one non-key attribute.
It is the “many” side in a many-one or many-many relationship.
What are some rules of thumb to distinguish between entities and attributes?
If something is a “thing” in its own right, it’s likely an entity (e.g., patient).
If something is a “detail” about some other “thing,” it’s likely an attribute (e.g., name).
If something is a “detail” correlated among many “things,” it’s likely an entity (e.g., patient history).
What is the underlying principle behind distinguishing between entities and attributes?
The distinction between entities and attributes is largely about avoiding redundancy. Entities represent distinct “things” with their own attributes, while attributes are details about those entities. This distinction helps ensure a well-organized and normalized database design.