Multivalued Attributes in DBMS

Attributes are significant in DBMS as it deals with the organization and formatting of data. Of all the attributes, multivalued attributes are somewhat different and they have to be understood properly. To help us understand the above idea in the subsequent sections of this article, we will also explain related key terminologies, and how multivalued attributes work with the help of examples.

Key Terminologies

1. Attribute

An Attribute can be a certain characteristic or ability that the entity may have. In the case of a database table, it is a distinct column that describes one aspect of a record, for example, a student's identity or the cost of an item.

2. Entity

A real object that has a real-life meaning and which may exist in reality and may be stored in a database. For example, an “Order” entity may specify details of what the consumer has purchased. When it comes to relational databases, one is likely to find an entity in relation to a table.

3. Relation

It is a connection or interaction between two or more entities. This outlines how various entities are related. When it comes to developing relations in a database most often keys called foreign keys are used. A foreign key is a field present in a table that is used to refer the primary key of another table.

4. Primary Key

Primary Key can act as a unique identifier of an entity within our database. It can help to prevent redundancy of the records as well as take a shorter time to look for a particular piece of information. For example, consider a library management system - The "ISBN" number on the books is usually used as the primary key that can be used to retrieve information about any specific book.

What are Multivalued Attributes?

In contrast to its single-valued counterpart, a multivalued attribute allows more than one value to be stored for a single entity instance. In simpler words, it permits an entity to have several values assigned to a given attribute.

• They show how an entity and the values it can have for an attribute are related in a one-to-many relationship
• Entity-Relationship (ER) diagrams use a double ellipse shape to represent them in order to differentiate them from single-valued characteristics.

Examples

Example-1: Suppose there is an attribute in "student " table called " Interests " which can contain multiple values of the student's interests. This attribute would display the various interests that students would have like “sports”, “music”, “programming etc. Due to the multiple-values functionality of this attribute, the database will be able to contain a number of information regarding the student's preferences and activities.

In the above example , " Roll no." , " Name " are single valued attribute whereas Interests is a multivalued attribute.

Example-2:

Suppose you have a table called " Movie ", which may include the details like "Director " ," Title" and the " release year " , but what about the actors who give life to the characters of the script or the technicians who put in their best effort to make the movie what it is? Looking at the kind of properties that have already been created, there’s one that might be of value – “Cast & Crew”. The database might have the list of all performers, directors, producers, all the artists who draw the special effects that were used in the film among other things giving it various uses. This adds a little more understanding of the people who participated in creating the movie.

Benefits of Multivalued Attributes

• Flexibility: Using multivalued attributes some of the values may contain more than one input, such as phone numbers or emails of a particular contact or rather several related data of entities, therefore they prove to be more flexible.

• Normalization: Normalization is extremely useful when multivalued attributes are present since they can be used in order to prevent redundancy and divide data into many different tables so that each piece of data would be stored in another table. These relationships further help in maintaining the data consistency and integrity as each and every attribute value is linked using keys. When data is organized in to third normal form (3NF), it means data entries in each table represents a single idea, hence minimizing problems in data manipulation.

Drawbacks of Multivalued Attributes

• Data Integrity Challenges: Regarding the rules of data integrity, handling of multivalued attributes may also create some difficulties in the proper management of data consistency; while modifying or removing some data, it may lead to the modifying of one or several more associated values that will potentially create inconsistency.

• Query Complexity: While using search and update queries on records associated with multivalued attributes most often necessitate more complex SQL statements or some sort of software logic that sometimes can prove disadvantageous in development and support.

• Normalization Overhead: Depending on the specified multivalued attributes, the normalization process will lead to higher costs of having greater number of tables as well as relation. This can result in making the query complicated and possibly resulting to poor performance since in most cases, more joins are used and cross-references are implemented among tables.

Conclusion

It can be concluded that although multivalued attributes can present certain difficulties, at the same time it is comprehensible to model entities where the number of values can differ for a given attribute. The main conclusion is that one can easily control these attributes with the help of appropriate normalization methods and data modeling approaches, thus achieving a high level of database organization.