tree
NDM (Network Data Model) and HDM (Hierarchical Data Model) are two types of database models used in DBMS. NDM organizes data in a graph structure, allowing for complex relationships and many-to-many connections, while HDM arranges data in a tree-like structure with a strict parent-child hierarchy. Both models represent data relationships but differ in their organization and access methods, with NDM offering more flexibility in relationships compared to the more rigid structure of HDM.
A graph is an abstract data type that can effectively represent many-to-many relationships. In a graph, nodes (or vertices) represent entities, while edges represent the connections or relationships between them, allowing for multiple connections between different nodes. This structure is ideal for modeling complex relationships, such as social networks or collaborative systems, where numerous entities interact with one another in various ways.
Many to many relationship in DBMS is usually a mirror of the real-life relationship between objects that tables represent.
A 232-bit data structure contains 4,294,967,296 bits.
Entity Relationship Diagrams (ERD's) are a way of diagrammatically showing entities in an organisations and how they relate to each other. ERD's show detailed representations of the information that is used in a system and how it relates to other data. There are a number of symbols that represent the entities and the relationships between them; the relationship can be a one to many relationship, many to many or one to one.
tree
Table is where the data is stored and in a well designed schema a table represents some real world object such as CUSTOMER, ORDER, etc., Now the real world objects have relationships. For example, a CUSTOMER has many ORDERS. To represent this relationship a database relationship was invented.
There are many such systems of diagrams used to aid program design (e.g. data flow diagrams, entity relationship diagrams, control flow diagrams, flowcharts).
A complete data bus structure is responsible to do this
Cardinality relationship refers to the quantitative relationship between two entities in a database or set theory, indicating how many instances of one entity can or must be associated with instances of another entity. In a relational database, cardinality can be classified into types such as one-to-one, one-to-many, and many-to-many. This concept helps in defining the structure and constraints of data relationships, ensuring data integrity and efficient querying. Understanding cardinality is crucial for designing effective database schemas.
how many numbers your data is away from your mean
That is done in a many to many relationship.