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Most people refer to data as computer information, whether it’s being transmitted or stored. However, numbers or texts on a piece of paper, bits, and bytes inside an electronic memory device, or facts inside the human mind can also be classified as data. Data structure refers to a collection of facts and figures, a set of values or values of a distinct format that reference a precise combination of items.  

What Is a Data Structure: An Exact Definition

A data structure is a professional way of storing, organizing, processing, and retrieving data. There are different types of structures designed to arrange data for different purposes. This makes it easy for users to have access to the data they need.

A data structure organizes the information in a way that is easily understandable by both machines and humans. In computer science and programming, data structures are designed to be used with specific algorithms. Each structure has information about data values, data relations, as well as functions that can be applied to the data.  

Types and Examples Of Data Structures

Data structures are used differently to solve both mathematical and logical problems in our daily lives. With the use of a data structure, one can organize and operate a very large amount of data within a relatively short time. There are two main types of data structures: primitive and non-primitive.


These types of data structures operate directly, as per what the machine instructs them to do. They hold one value only and consist of data types such as float, int, pointers, and double among others.


These are complex types of data structures that originate from primitive ones. They are classified into linear and non-linear data structures.

Linear Data Structures

data structure
Well-organized data structures are key to designing efficient algorithms.


In a linear data structure, the data is arranged linearly or sequentially where the current element is always attached to its previous and next elements. The linear data structure can be Static, where the data has a fixed memory size making it easy to access the elements, or Dynamic, where the memory size is not fixed, allowing for random updates of the data. 

The linear data structure consists of the following:


This is a linear data structure in which items are collected and stored in adjoining memory locations. The main idea is to have all the same data types together in one place. This allows a large amount of data to be processed in a very short time.

Arrays have different operations such as searching, inserting, sorting, and deleting, among others. Below are operations done in an array:

  • Traverse – Going through the elements before printing them.
  • Search – Doing a deep dive for elements within the array. The elements can be searched by their index or value.
  • Update – Keeping the existing elements within a given index up to date.

The insertion and deletion of elements within the array cannot be done, since all the elements are fixed in size. If one wants to insert or delete an element, they are required to create a new array and increase the size.

Application of Arrays
  • Used to solve matrix problems
  • Implementation of database records
  • Used to schedule CPU
  • Applied as a lookup table in computers
  • Used to process an array of speeches
  • A multidimensional array is used to display the computer screen
  • Used in management systems like a library, students’ portals, and parliament
  • To save images in a different dimension
Linked List

This is a linear data structure where elements are not stored at contiguous memory locations. All the elements here are linked using references or pointers. Linked lists are categorized as a singly-linked list, doubly-linked list, circular linked list, and doubly circular linked list. This data structure uses extra memory to store the links.

  • Singly-linked list – Items can only be traversed in the forward direction.
  • Doubly linked list – Items can be traversed in both backward and forward directions. Nodes have an additional pointer called PREV, and it points toward the previous node.
  • Circular linked lists – The PREV pointer points toward the tail and the next pointer towards the head of the nodes.
Linked List Operations
  • Search – Find the first element containing a specific key from the assigned linked lists using linear search.
  • Insert – Introduce a key to the linked list. This can be done at the beginning of the list, at the end, or in the middle of the list. 
  • Delete – This removes a specific element from a specified list. Deletion can only be done in three steps: deleting from the beginning, from the end, and from the middle of the list.
  • Used in Round-Robin scheduling to keep track of the turn in the multiplayer games
  • They store previously visited web pages
  • Display social media feeds

This is a linear data structure where there is a particular order in which every operation is performed. The order is “the last in is the first out.” Here, data can only be entered and retrieved from one end, which is called the push-and-pop operation. Operations that are performed under stack are recursion, sorting, deleting, and much more.

Stack Operations
  • Push – This is inserting an element at the top of the stacks.
  • Pop – The topmost element is deleted and then returned back.
  • Peek – Returning the element at the top without deleting it.
  • isEmpty – Confirming that the stacks are empty.
  • isFull – Checking if the stacks are full.
  • Call logs on mobile phones use a stack data structure
  • Browsers use stacks to keep a list of every previously visited site
  • Used in memory management
  • Convert infix to postfix expressions
  • Used in media players to play the next song 

This is a linear data structure that uses a particular order “first in, first out’ to perform its operations. All the data that has been sorted first will be accessible first and entering and retrieving data is done from multiple ends.

A good example is a queue for a particular consumer; the person who came first is always served first. To access a file here you have to remove all the files that were added before it. 

Operations in Queue
  • Enqueue – Add an element that is at the end of the queue
  • Dequeue – Delete an element that is at the beginning of the queue

Non-Linear Data Structure

This is the second type of non-primitive data structure where the data elements are not sequential. Here, it’s hard to navigate all the elements in one go. They consist of the following:

data structure
In a data tree, each child can be treated like the root node of its own subtree, which makes recursion a useful technique for tree traversal.


This is a non-linear data structure in which elements are arranged in a tree-like structure, with the top node referred to as the root node. Each node contains a variety of unsorted data.

It is made up of central nodes, structural nodes, and sub-nodes. These nodes are connected using edges. Binary tree, Binary search tree, AVL tree, and B-tree are the different types of tree-like.

Attributes of Binary Search Tree
  1. Key – The value that is stored within the node
  2. Left – Pointers pointing towards the left child
  3. Right – Pointers pointing towards the right child
  4. P – Pointers towards the mother node
  • Helps in game development
  • Indexing databases
  • Domain Name Server
  • Social networking sites

This is a non-linear data structure that has vertices and edges. It has a restricted number of vertices and edges that connect the nodes. This data structure is mainly used to solve programming problems that are complex and challenging. The vertex that has the least eccentricity is viewed as the center of the graph.

Directed Graphs – When all the edges’ directions indicate the start and the end vertex.

Undirected Graphs – All the edges don’t have a specific direction. An edge that is not connected to anything in the graph is considered to be isolated. 

  • Used to present computation flow
  • Used in modeling graphs
  • Used to represent web pages and Google links by the search engine
  • Resource allocation graphs are used in operating systems
  • A social network where the users are the nodes and the friendships within the network become the edges
Hash Tables

This is a data structure that stores values with the same key associations. It is efficient with lookup because of the relationship between the keys. Due to this fact, it’s efficient in searching and inserting, without considering the size of the data. 

Hash tables have one function named hash function (h) that is used to overcome the aforementioned problems.

Applications of Hash Tables
  • Implementation of database index
  • Implementation of associative arrays
  • Set data structure implementation

How to Choose a Data Structure

Data structures are chosen depending on the operations and complexity of the application or the software under development. Different data structures offer different solutions and therefore it’s wise to choose the most convenient data structure and an engineer. 


It’s paramount to understand what operation you want to be performed by the data structure, like retrieval, deletion, updating, insertion, and traversal. What operation will be performed frequently? What operation will not be used at all?

These types of questions help identify if the data structure meets all your needs and whether you can combine multiple structures to meet all your needs, as well as confirm if the structures are going to be fast or slow when used.


The question here is which data structure will be the most useful and efficient when it’s big. A good data structure should be able to handle any size of the structure or data.

Memory Control

Static memory data structures take a fixed amount of memory upon their installation and cap the amount of data to be added. On the other hand, dynamic data structures give the user the mandate to allocate, release and reallocate memory when the program is in use. However, programs like Python and JavaScript do the data allocation for the user regardless of the type of structure being used.

Uses of Data Structures

Let’s look at the application of data structures below.

Data Implementation

data structure
Implementing a structure means constructing a logical way to interpret or order the related data for proper access.


Data structures are mainly used in the implementation of abstract data in the physical form. This makes them a vital part of creating and running effective software. They also help in algorithm design. Several early programming languages, like C and C++, gave programmers the ability to delineate their data structures. 

Data Storage

Software engineers are using algorithms that are fully coupled with the type of data structures they desire, like lists and queues. Data structures are also used to store data. They specify the collection of traits and the structures used to store records in a database system.

They also manage resources and services. The resources and services of the operating system are enabled through the use of data structures, like linked lists of memory allocations. 

Sort and Order Data

Data structures are used to sort and order data. A data structure, such as a binary search tree, offers an efficient way of sorting data that is used as tags. Lastly, large data applications and software use data structures to allocate and manage data stored within different data sites, ensuring there is maximum scalability and performance.

Importance of Data Structures

It helps in effective data management. A thoughtful and wise data structure selection can improve the performance of an algorithm or computer program, making it more useful.

Handling Complexity

An increase in computer programming and the rise in data usage can affect the execution of some applications and lower the processing speed, searching data, and handling of multiple requests. To manage this menace, data structures are used to help the computer run more effectively.

Systematic use of Memory

Optimization occurs when data structures memory. For example, one can use linked lists and arrays when not sure of the size of the data. The data can also be cleared when it’s no longer in use.

Ability to Reuse

Once a specific data structure has been launched, it can be re-used at any discrete position. These implementations can be put into libraries that allow different clients to use them.


A data structure is the foundation of data types that are abstract. In the abstract data type, the operations are supposed to be understood.

It’s important to choose the most fitting data structure for the data to be worked on. An ill-suited data structure can lead to the slow running of a program or the unresponsiveness of the code. Before choosing the right data structure, consider the following questions:

  • What type of information will be stored there?
  • How will the stored information be used?
  • Where is the data supposed to be kept after it has been designed or created?
  • Is there a better way to organize the data?

Types of Data

If data structures are the blocks that build the base of the computer programs, then data types are the blocks that build data structures. Different types of data include:

  • Boolean – This is the storage for the logical values of what is true or false.
  • Integers – They vary in size and hold a wide range of values. For example, an 8-bit integer holds values between 128 and 127.
  • Floating-point numbers – They store the representation of real numbers in formulas.
  • Pointers – These are the reference points that refer to other values.
  • String – This represents an array of characters that are followed by a stop code, usually of a “0” value.

Real-Life Applications of Data Structures

  • When watching something on TV, that display is a multidimensional array.
  • Question-numbering during an online exam where you can’t skip a number is an application of arrays.
  • The arrangement of book titles in a digital library management system is an application of arrays.
  • Used in image viewer where the previous and next images are linked by the previous and next buttons.
  • In a music playlist, the current song being played is linked to the previous and the next one.
  • A pile of plates uses stacks.
  • Redo and undo buttons in Microsoft Word are applications of stacks.
  • When reducing the workforce, companies use the last hired, first fired criteria. These are stacks.
  • The browser history of visited web pages is an example of stacks in use.
  • Printers, car wash, and wedding emails use the queue structure.
  • Scientific computations and the ranking of pages employ graph structure.


How data is organized is referred to as data structure. The structure also allows the user to interact with the data in a specified way. Choosing the right data structure is determined by the program and the algorithm one is working with. Making the right data structure selection is very important to every software engineer. 

What Is a Data Structure, And How Does It Work? FAQs (Frequently Asked Questions) 

What are data structures, and why are they important?

Data structures are a way to organize and store data in a computer program so that it can be accessed and manipulated efficiently. They are important because they allow for faster and more effective data processing, which is essential for many applications.

What are the most commonly used data structures?

Some of the most commonly used data structures include arrays, linked lists, stacks, queues, trees, and graphs. Each of these data structures has its own strengths and weaknesses and is suited for different types of data and applications.

How do data structures differ from algorithms?

While data structures are concerned with how data is organized and stored, algorithms are concerned with how data is processed and manipulated. In other words, data structures provide the foundation for algorithms to operate on.

What is the time complexity of a data structure operation?

The time complexity of a data structure operation refers to how much time it takes to perform that operation. This is important because it allows us to evaluate the efficiency of different data structures and algorithms and choose the best one for a particular task.

How do data structures relate to memory management?

Data structures are closely related to memory management because they determine how data is stored in memory. Efficient memory management is essential for good performance, and choosing the right data structure can help minimize memory usage and optimize program speed.

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