Each entity contains members, which are the rows of master data that you manage. Models can contain as many entities as you want to manage. Each entity should group a similar kind of data.
For example, you might want an entity for all of your corporate accounts, or an entity for your master list of employees.
Typically, there are one or more central entities that are important to your business, and to which other objects in the model relate. For example, in a Product model, you could have a central entity called Product and entities called Subcategory and Category that relate to the Product entity.
However, you do not need to have a central entity. Depending on your needs, you might have several entities that you consider to be of equal importance. You can think of an entity as a table that contains master data, where the rows represent members and the columns represent attributes.
Entities can be used to build derived hierarchies, which are level-based hierarchies based on multiple entities. Entities can also be enabled to contain explicit hierarchies ragged structures based on a single entity and collections one-off combinations of subsets of members. In my initial design I was already unknowingly applying normalization, because it just seems like common sense to me.
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Question feed. Each entity is described by a set of attributes e. Each attribute has a name, and is associated with an entity and a domain of legal values. However, the information about attribute domain is not presented on the ERD. In the entity relationship diagram, shown in Figure 8. There are a few types of attributes you need to be familiar with. Some of these are to be left as is, but some need to be adjusted to facilitate representation in the relational model.
This first section will discuss the types of attributes. Later on we will discuss fixing the attributes to fit correctly into the relational model. Simple attributes are those drawn from the atomic value domains; they are also called single-valued attributes. Composite attributes are those that consist of a hierarchy of attributes. Using our database example, and shown in Figure 8. Multivalued attributes are attributes that have a set of values for each entity.
Derived attributes are attributes that contain values calculated from other attributes. An example of this can be seen in Figure 8. Age can be derived from the attribute Birthdate. In this situation, Birthdate is called a stored attribute, which is physically saved to the database. An important constraint on an entity is the key. The key is an attribute or a group of attributes whose values can be used to uniquely identify an individual entity in an entity set.
A candidate key is a simple or composite key that is unique and minimal. It is unique because no two rows in a table may have the same value at any time. It is minimal because every column is necessary in order to attain uniqueness.
The primary key is a candidate key that is selected by the database designer to be used as an identifying mechanism for the whole entity set. It must uniquely identify tuples in a table and not be null. The primary key is indicated in the ER model by underlining the attribute. A secondary key is an attribute used strictly for retrieval purposes can be composite , for example: Phone and Last Name.
A foreign key FK is an attribute in a table that references the primary key in another table OR it can be null. Both foreign and primary keys must be of the same data type. A null is a special symbol, independent of data type, which means either unknown or inapplicable.
It does not mean zero or blank. Clearly, there may be several possible keys that could be used to identify an entity; we choose one of the alternative, or candidate , keys to be our main, or primary , key. You usually make this choice based on how confident you are that the attribute will be non-empty and unique for each individual entity, and on how small the key is shorter keys are faster to maintain and use.
In the ER diagram, attributes are represented as labeled ovals and are connected to their owning entity, as shown in Figure Attributes comprising the primary key are shown underlined. The parts of any composite attributes are drawn connected to the oval of the composite attribute, and multivalued attributes are shown as double-lined ovals. Similarly, a product price could be a positive rational number.
Attributes can be empty; for example, some customers may not provide their telephone numbers. You should think carefully when classifying an attribute as multivalued: are all the values equivalent, or do they in fact represent different things? The sales database requirements may specify that a product has a name and a price. To distinguish between products, we can assign a unique product ID number to each item we stock; this would be the primary key.
Each product entity would have name, price, and product ID attributes. This is shown in the ER diagram in Figure Entities can participate in relationships with other entities. For example, a customer can buy a product, a student can take a course, an artist can record an album, and so on. Like entities, relationships can have attributes: we can define a sale to be a relationship between a customer entity identified by the unique email address and a given number of the product entity identified by the unique product ID that exists at a particular date and time the timestamp.
Our database could then record each sale and tell us, for example, that at p. Different numbers of entities can appear on each side of a relationship. For example, each customer can buy any number of products, and each product can be bought by any number of customers.
This is known as a many-to-many relationship. We can also have one-to-many relationships. For example, one person can have several credit cards, but each credit card belongs to just one person. Looking at it the other way, a one-to-many relationship becomes a many-to-one relationship; for example, many credit cards belong to a single person. Finally, the serial number on a car engine is an example of a one-to-one relationship; each engine has just one serial number, and each serial number belongs to just one engine.
We often use the shorthand terms , 1:N, and M:N for one-to-one, one-to-many, and many-to-many relationships, respectively. The number of entities on either side of a relationship the cardinality of the relationship define the key constraints of the relationship.
There are many relationships that may at first seem to be one-to-one, but turn out to be more complex. For example, people sometimes change their names; in some applications, such as police databases, this is of particular interest, and so it may be necessary to model a many-to-many relationship between a person entity and a name entity.
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