A key attribute is an attribute that uniquely identifies a record in a database table. Non-key attributes are attributes that are not used to uniquely identify records, but provide additional information about the data.
Data dependency in DBMS refers to the relationship between different data elements within a database. There are three main types: functional dependency (one attribute determines another), partial dependency (part of a composite key determines other attributes), and transitive dependency (dependency between non-key attributes). Understanding data dependencies is crucial for database normalization and maintaining data integrity.
Attribute is the property of entity.The composite attribute is like address(where street no,house no,town name all include).Composite key is also an attribute,but only which attribute are work as a unique identifier. Example:> In an ERD if vendor placed with orders then order(order day, order number) vendor(vendor code,vendor address) Here, order and vendor both are entity and order number, vendor code both are Composite key(because those are unique)but vendor address is a Composite attribute and order day(may be not unique)is an attribute only. So, we can conclude that all attribute not Composite key.
A primary key is an attribute (or combination of attributes) that uniquely identifies each row in a relation. A primary key is designated by underlining the attribute name. The primary key of an entity set allows us to distinguish among the various entities of the set. A foreign key is an attribute in a relation of database that serves as the primary key of another relation in the same database.
Yes, a unique identifier is also called a record key. It is a field or attribute that distinguishes one record from another in a database or dataset.
Prime attribute are part of any candidate key. Non-prime attribute are not part of any candidate key.
A key attribute is an attribute that uniquely identifies a record in a database table. Non-key attributes are attributes that are not used to uniquely identify records, but provide additional information about the data.
a key to a different table
A relation violates third normal form (3NF) if it has a transitive dependency where a non-prime attribute depends on another non-prime attribute (which itself is not a candidate key). This means that a non-prime attribute is functionally dependent on another non-prime attribute rather than on a candidate key.
Attributes can be classified as identifiers or descriptors. Identifiers, more commonly called keys or key attributes uniquely identify an instance of an entity. If such an attribute doesn't exist naturally, a new attribute is defined for that purpose, for example an ID number or code. A descriptor describes a non-unique characteristic of an entity instance. An entity usually has an attribute whose values are distinct for each individual entity. This attribute uniquely identifies the individual entity. Such an attribute is called a key attribute. For example, in the Employee entity type, EmpNo is the key attribute since no two employees can have same employee number. Similarly, for Product entity type, ProdId is the key attribute. There may be a case when one single attribute is not sufficient to identify entities. Then a combination of attributes can solve this purpose. We can form a group of more than one attribute and use this combination as a key attribute. That is known as a composite key attribute. When identifying attributes of entities, identifying key attribute is very important.
A relation is in second normal form (2NF) if any of the following conditions apply: The primary key consists of only one attribute No non-primary key attribute exists in the relation Every non-primary key attribute is functionally dependent on the full set of primary key attributes
Data dependency in DBMS refers to the relationship between different data elements within a database. There are three main types: functional dependency (one attribute determines another), partial dependency (part of a composite key determines other attributes), and transitive dependency (dependency between non-key attributes). Understanding data dependencies is crucial for database normalization and maintaining data integrity.
It is an attribute that does not occur in some candidate key.
transitive dependency
Transitive Dependency
The purpose of normalizing data in DBMS is to reduce the data redundancy and increase the consistency of data. a) Partial dependency: non-prime attribute ( field) depends on other non-prime attributes b) Functional dependency c) Transitive dependency
Nonloss-decomposition is data normalization without the loss of information.