It is important for anybody working in the field of data science to know how databases work. My name is Sabreena. Functional dependency is one of the most basic concepts to understand when it comes to database management. It helps in the design, normalization, and optimization of relational databases, which makes it pivotal for database management systems (DBMS). In this article, we will delve deep into what functional dependency is, how it works, and what role it plays in DBMS. We will also learn about Armstrong’s Axioms and ways to identify these dependencies.
A functional dependency is a relationship between two sets of attributes in a relational database. Generally speaking, if a set of attributes X can uniquely determine another set of attributes Y, we say that Y is functionally dependent on X. This is denoted as X → Y.
For example, consider a Student
table with the following attributes: StudentID
, StudentName
, Course
, and Instructor
. If each course is taught by only one instructor, then the attribute Course
can determine the attribute Instructor
.
Course→Instructor\text{Course} \rightarrow \text{Instructor}Course→Instructor
This means if we know the course, we can determine the instructor uniquely.
Functional dependencies are essential for database normalization. They aim to reduce redundancy and improve data integrity in databases. They also prevent anomalies during database updation. More importantly, they help in identifying the correct schema design by ensuring that each attribute is stored in the appropriate table.
There are 3 types of functional dependencies in DBMS.
A functional dependency X → Y is trivial if Y is a subset of X.
Example: StudentID, Course→Course\text{StudentID, Course} \rightarrow \text{Course}StudentID, Course→Course
A functional dependency X → Y is non-trivial if Y is not a subset of X.
Example: Course→Instructor\text{Course} \rightarrow \text{Instructor}Course→Instructor
A functional dependency X → Y is completely non-trivial if X and Y have no attributes in common.
Example: StudentID→StudentName\text{StudentID} \rightarrow \text{StudentName}StudentID→StudentName
Armstrong’s Axioms are a set of rules used to infer all the functional dependencies on a relational database. They are:
Additional derived rules include:
To identify functional dependencies, you can:
Functional dependencies are a must for effective database design and the normalization of relational databases. Data scientists and database administrators can ensure data integrity, reduce redundancy, and optimize database performance by applying them. The process of identifying and managing these dependencies becomes more systematic with tools like Armstrong’s Axioms. In short, whatever you have learned in this article about functional databases can help you create an efficient and reliable database system.
A. A functional dependency is a constraint between two sets of attributes in a database where one set can uniquely determine another.
A. They are crucial for normalization, which reduces redundancy and ensures data integrity.
A. Armstrong’s Axioms are a set of rules used to infer all functional dependencies in a relational database.
A. In a Student
table, Course → Instructor
means that each course is taught by a single instructor. This is an example of a functional dependency.
A. By analyzing data, understanding business rules, consulting documentation, and using SQL queries.
Sabreena Basheer is an architect-turned-writer who's passionate about documenting anything that interests her. She's currently exploring the world of AI and Data Science as a Content Manager at Analytics Vidhya.
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