Logical Data Model Concepts
The logical design is about mapping of entities, relationships, and along the last part Database — Modeling: Entity Relationship Diagram (ERD) (Part 5) In our example, we had a one-to-many recursive relationship called. Relationship cardinality can be of three types: one-to-many, one- to-one, A diagram depicting a logical data model is known as an entity-relational diagram. I think you mean something like in the image below. Crow's foot notation is used here but more notations are possible such as idef1x. Most ER.
While ER models are mostly developed for designing relational database in terms of concept visualization and in terms of physical database design, there are still other situations when ER diagrams can help.
Here are some typical use cases. Database design - Depending on the scale of change, it can be risky to alter a database structure directly in a DBMS.
To avoid ruining the data in a production database, it is important to plan out the changes carefully. ERD is a tool that helps. By drawing ER diagrams to visualize database design ideas, you have a chance to identify the mistakes and design flaws, and to make correction before executing the changes in database. Database debugging - To debug database issues can be challenging, especially when the database contains many tables, which require writing complex SQL in getting the information you need.
By visualizing a database schema with an ERD, you have a full picture of the entire database schema. You can easily locate entities, view their attributes and to identify the relationships they have with others. All these allows you to analyze an existing database and to reveal database problem easier. Database creation and patching - ERD tool like Visual Paradigm supports database generation tool that can automate the database creation and patching process by means of ER diagrams.
So, with this ER Diagram tool your ER design is no longer just a static diagram but a mirror that reflects truly the physical database structure. Aid in requirements gathering - Determine the requirements of an information system by drawing a conceptual ERD that depicts the high-level business objects of the system.
One-to-many (data model) - Wikipedia
Such an initial model can also be evolved into physical database model that aids the creation of relational database, or aids in the creation of process map and data flow model. In this section we will go through the ERD symbols in detail. Studentobject e. Invoiceconcept e. Profile or event e.
One-to-many (data model)
In ERD, the term "entity" is often used instead of "table", but they are the same. When determining entities, think of them as nouns. In ER models, an entity is shown as a rounded rectangle, with its name on top and its attributes listed in the body of the entity shape. Entity Attributes Also known as column, an attribute is a property or characteristic of the entity that holds it. An attribute has a name that describes the property and a type that describes the kind of attribute it is, such as varchar for a string, and int for integer.
The ER diagram example below shows an entity with some attributes in it. Primary Key Also known as PK, a primary key is a special kind of entity attribute that uniquely defines a record in a database table. In other words, there must not be two or more records that share the same value for the primary key attribute. The ERD example below shows an entity 'Product' with a primary key attribute 'ID', and a preview of table records in database.
Foreign Key Also known as FK, a foreign key is a reference to a primary key in table. It is used to identify the relationships between entities. Note that foreign keys need not to be unique.
A relationship verb phrases may be established for both directions of a relation between two entities. The entity types associated through a relationship fulfill two roles: One entity is a parent entity. The second entity is a child entity. The parent entity shares it identity with the child entity. The child entity inherits the primary key of the parent entity type and is referred to as a dependent entity type. The attribute shared from a parent to a child entity type is called a foreign key.
In an entity diagram an attribute name that is a foreign key is designated with a " FK " suffix. In a relational data model there are two ways a parent and child entity type may be related.
The first way is an identifying relationship. An identifying relationship means that the child entity's primary key inherits its parent entity type's primary key. That means that the child entity type's existence is dependent on its parent entity type's existence.
If the parent entity type is deleted in this scenario, this scenario, the child is deleted. Conversely a child entity type cannot be inserted until the parent it references is inserted. In an entity diagram, an identifying relationship is signified by a solid line between the parent and child entity types.
The second way parent and child entity types may be related is through a non-identifying relationship. In a non-identifying relationship, the parent entity primary key is inherited by the child entity as a non-primary key attribute.
This means that the child entity references its parent entity type but is not dependent on the parents existence for its own existence. From a relational database point of view this means that the inherited attribute may be null -- that is point to nothing.
In an entity diagram, a non-identifying relationship is signified by a dashed line between the parent and child entity types.Model Relational Data in Firestore NoSQL
Relationships incorporate an additional property between parent and child entity types called cardinality. Cardinality expresses the count of child entity type instances that may exist for a parent entity type. For example a Brand may apply to zero, one or many Item entity type instances. Conversely, an Item may be referred to by zero or one Brand. These cardinalities are illustrated in the diagram below. There are a variety of ways cardinality is used to express the relative counts of parent entity types to children entity types and they are presented in the Data Model Methodology and Notation Topic.
It also illustrates how foreign keys and cardinality are presented in an entity diagram. It introduces Owned Attributes which are attributes that are NOT inherited from another entity type and are not part of an entity type's primary key.
Figure 96 - Sample Entity, Attribute and Simple Relationship In addition to cardinality, there is a special type of relationship called a subtype that allows several child entity types to inherit a common parent entity type characteristics. This is illustrated in the next diagram. A retail transaction definition is shown in the yellow block. As modeled here, a RetailTransaction may have zero, one or many RetailTransactionLineItem entity instances associated with it.
The RetailTransactionLineItem entities are dependent entities because a line item cannot exist without a retail transaction header. A retail transaction line item provides a set of attributes including line item number that all subtypes share i. A RetailTransactionLineItem entity type instance may be one and only one subtype. This relational concept of subtype is analogous to the inheritance used to model classes and objects in object oriented design.
For this example subtype child entity types efficiently represent a retail transaction and the different kinds of line items needed to capture item, discount, tax and tender data. The sample receipt shows how each subtype of RetailTransactionLineItem reflects different sales receipt line items. Figure 97 - Entity Subtype Relationship Example Domains A domain is a named type of data representation that may apply to one or more attributes.
Data representation defines a data type such as integer, string, floating point, date, time or other standard data type or an extended definition that assigns custom properties and constraints to a base data type.
Domains enable retail-specific data types to be derived from SQL base data types. The creation of domains can also be used to define constraints that values assigned to an attribute assigned to a domain. Data Model Semantics Semantics is the branch of linguistics and logic concerned with meaning. Logical models, in addition to identifying entities, attributes, relationships and domains define what each instance of these object means.
These definitions provide the semantic content of a data model are are essential to the business relevancy of a relational model. The diagram below illustrates the assignment of a definition to the ItemID attribute of Item. Definitions should be expressed in business terms and reflect the business concepts represented by a data model entity, attribute, relationship, domain and other model objects.
Logical Data Model
Data models are not just for information technologists. Data models are a prerequisite to operating a retail enterprise in today's business climate. Information as A Currency and Asset Retailing in the 21st century is as much about managing information as it is about managing cash, merchandise, customers, stores, vendors and other "real world" business assets.
Most retail decision makers rely on information to make decisions because they can not personally visit and observe every retail site personally. To be useful, information has to be identified, named, described and organized into a coherent structure so it can be understood by decision makers. Data modeling provides a formal set of tools and procedures to make information useful.