Functional Dependency: What It Is and Its Benefits

By Indeed Editorial Team

Published June 2, 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

With the increased use of digital record-keeping, most businesses use databases to store files, transaction records, employee and customer profiles, and other critical data. Functional dependence can create numerous parameters, rules, and features inside a database system to assist with sorting, managing, storing, and retrieving data. Learning more about functional dependence can help you develop skills that might benefit you in a database management or information technology role.

In this article, we define functional dependency, review some key related terms, discuss some of its benefits, explore its rules and types, define dependency management, and provide some examples.

What is a functional dependency?

Functional dependency (FD) occurs when one property uniquely determines the value of another. You can use it with a primary key and a non-key attribute inside a table or data collection. Functional dependence operates as a constraint between two sets of characteristics and is often critical when building database parameters and functions for a business or organization that stores and manages its data.

An arrow is typically used to indicate functional dependency. For instance, if you label one characteristic X and another Y, and X's FD is on Y, the formula is:

X→Y

Key terms of FD

FD and database management often have specific terminology. Here are several key terms used in FD:

  • Axiom: This is a collection of rules for inferring functional dependencies within relational databases.

  • Decomposition: The term decomposition refers to the process of separating a table into two entities defined by the same primary key attribute for improved database accuracy. For instance, if you use the same set of employee numbers across various national offices, maintaining distinct tables helps ensure that employee number 100 doesn't acquire numerous employee names and their associated profile information.

  • Dependent: A dependent refers to the attribute presented on the right side of the FD diagram.

  • Determinant: The determinant is the attribute presented on the left side of the FD diagram.

  • Normalization: Normalization is a strategy for organizing data to avoid redundancy and prevent insertion, update, and deletion abnormalities. It's often a necessary component in developing a relational database.

  • Union: The term union implies that two distinct tables have the same primary key, combining them into a single table to help improve the data's integrity and accessibility. For instance, if you use employee numbers to construct two tables, one for location information and another for compensation information, merging the two columns can allow you to search an employee number once and evaluate both location and salary information concurrently.

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Benefits of FD

The benefits of FD and an overall database management system can help a business or organization achieve the following:

  • Prevent data redundancy: FD helps eliminate repeated data throughout a database or network of databases.

  • Maintain the quality and integrity of data: Because FD factors often result in a more effective and less redundant system, the quality and integrity of your data may also improve. Establishing functional dependence can result in the production of accurate and trustworthy data.

  • Reduce the risk of error: By better organizing and preserving information while storing records, data, and other transactions in a database with FD, you can decrease the occurrence of mistakes within documents and data sets.

  • Gain productivity and save costs: When you properly format files, documents, and transactions, it's usually possible to retrieve and access data more rapidly, resulting in cost savings for the organization or corporation. Rather than searching through several files or data sets, you can generally depend on reliable and organized data when using FD.

  • Define meanings and constraints of databases: FD often allows you to define parameters that constrain, limit, or govern the actions, storage, and accessibility of data.

  • Identify poor designs: FD helps you detect duplicated or absent data in other tables. Improper design implies that data modifications need several changes across tables, and functional reliance often reveals data discrepancies.

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Rules of FD

There are three rules of FD that can help you if you're considering a profession in database management:

  • Reflexive rule: This rule states that if X is a set of attributes and Y is its subset, then X holds a value of Y.

  • Augmentation rule: This rule adds attributes, though they rarely change the basic dependencies and states if X→Y holds and C is an attribute set, then XC→YC also holds.

  • Transitivity rule: Closely aligned with algebra's transitive rule, this rule states if X→Y holds and Y→Z holds, then X→Z also holds. With this rule, X→Y is the functional dependent that determines Y.

Various types of FD

In database administration, there are four basic categories of FD, including:

Multivalued dependency

Multivalued dependence, or tuple-generating dependency, occurs when a table has many independent, multivalued characteristics. It's frequently a complete constraint between two attribute sets included inside a table or relation. For instance, a vehicle manufacturer may continue to produce two paint colours, such as silver and red, in each model year after year, regardless of whether they introduce more colours. The year and colour characteristics rely on the automobile model property, resulting in a multivalued dependence.

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Trivial FD

A trivial FD is a table or data set dependency that occurs when an attribute, or group of attributes, functionally depends on the original one. If Y is a subgroup of X, the formula X→Y is a simple functional dependence. For instance, a data table containing employee identification (ID) numbers and names can often include the employee ID number as a subset of the total ID and name data.

Non-trivial FD

When no characteristics are subsets, non-trivial functional reliance occurs. For example, in X→Y, Y isn't a subgroup of X in non-trivial situations of functional dependency. Often, you may tailor your data sets and characteristics for specific purposes. The employee ID number may again be the main key attribute in a list of employee ID numbers, names, and locations, even though the name and location aren't subsets of the ID number.

Transitive dependency

Transitive dependence occurs when two functional dependencies form indirectly, most often because of software components and programming. For instance, if X is transitively dependent on Y, which transitively depends on Z, then X becomes transitively dependent on Z. Transitive dependency exists only when there are at least three qualities in the relationship.

What is dependency management?

Dependency management is a kind of project management software that helps you identify, prepare for, and handle project dependencies. There are several pieces of software with differing codes, but the fundamental functions include organizing tasks, assessing a task's relationship to one another, and determining which ways might assist a project manager in resolving dependencies to finish a project. These technologies may assist firms with work prioritization, process automation, and the establishment of rules for future projects.

Examples of FD

Here are two examples of how FD works in database management:

University student roster list

Here's an example of FD in a student roster list for you to consider:

Central Hills University maintains a database of student profiles that include personal information. The two properties are functionally dependent on data collection that contains both student names and social insurance number numbers (SINs). Because SINs are the unique and recognizable factor for each student, the student's name is functionally dependent on their SIN. The university adds these five new students and their SINs to the roster:

  • Rita Torres, 071-646-177

  • Timothy Davies, 614-789-441

  • Peter Keith, 069-724-999

  • Peter Keith, 617-011-323

  • Aubrey Smith, 011-989-874

Within the database and this attribute set, the SIN uniquely identifies a student, whereas the student's name doesn't uniquely identify a SIN, as shown by the name Peter Keith. Administrators communicate course schedules to these students using the FD feature, which helps guarantee that the right course schedule reaches each person named Peter Keith.

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Employee compensation review list

Here's an example of using FD for an employee compensation list:

SkyHigh Aviation conducts pay reviews for personnel in management positions throughout its network of destinations and evaluates managers, their location, and their salary using FD. The main key element in the data table is the employee number, which the compensation team utilizes to get the individual's name, location, and pay total. The employee number determines the employee's name, location, and compensation.

Employee number Employee nameLocationSalary
100Helen StewartToronto, ON$123,000
101Melanie PetersonVancouver, BC$88,000
102Ronald JacobsMontreal, QC$79,000

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