What is Data Structure: Types, Classifications and Applications

Data structures are an integral part of Computers used for the arrangement of data in memory. They are essential and responsible for organizing, processing, accessing, and storing data efficiently. But this is not all. Various types of Data Structures have their characteristics, features, applications, advantages, and disadvantages. So how do you choose which data structure to choose for a particular task? What is meant by the term Data structure? How many types of data structures are there and what are they used for?

We have got you covered. We have made a complete list of everything about what data structure is, what are the types of data structures, the classification of data structures, the applications of each data structure, and so on. In this article, we will discuss every aspect of each data structure to help you choose the best one in just minutes.

What is Data Structure:

A data structure is a storage that is used to store and organize data. It is a way of arranging data on a computer so that it can be accessed and updated efficiently. A data structure is not only used for organizing the data it is also used for processing, retrieving, and storing data. There are different basic and advanced types of data structures that are used in almost every program or software system that has been developed. So we must have good knowledge about data structures. 

How Data Structure varies from Data type:

We already have learned about Data structure. Many times what happens is that people get confused between data type and data structure. So let’s see a few differences between data type and data structure to make it clear.

Data type	Data structure
The data type is the form of variable to which the value can be assigned. It defines that the particular variable will assign the values of the given data type only.	Data Structure is a collection of different kinds of data. That entire data can be represented using an object and can be used throughout the program.
It can hold value not data. Therefore, it is data-less.	It can hold multiple types of data within a single object.
The implementation of data type is known as an abstract implementation.	Data structure implementation is known as concrete implementation.
There is no term time complexity in data type.	In data structure objects, time complexity plays an important role.
In case of data type, the value of data is not stored because it only represents the type of data that can be get stored.	While in the case of data structure, the data and its value actually acquire the space in the computer’s main memory. Also, a data structure can hold different kinds and types of data within one single object
Data type examples are int, float, double	Data structure examples are stack, queue, tree

Classification of Data Structure: 

Data Structure has many different uses in our daily life. There is much different data structure which is used to solve the different mathematical and logical problem. By using data structure one can organize and process a very large amount of data in a relatively short period. Let’s see different data structure which is used in different situations. 
 

• Linear data structure: Data structure where data elements are arranged sequentially or linearly where each and every element is attached to its previous and next adjacent is called a linear data structure. 
  Examples of linear data structure are array, stack, queue, linked list etc.
  • Static data structure: Static Data structure has fixed memory size. It is more easier to access the element in static data structure. 
    Examples of this data structure is array.
  • Dynamic data structure: In Dynamic Data Structure the size is not fixed, the size can be randomly updated during run time which may be considered efficient with respect to memory complexity of the code. 
    Examples of this data structure is queue, stack, etc.
• Non-linear data structure: Data structure where data elements are not sequentially or linearly are called non-linear data structures. In non-linear data structure we can’t traverse all the elements in single run only. 
  Examples of non-linear data structure are trees and graphs.

Arrays:

An array is a linear data structure and it is a collection of items stored at contiguous memory locations. The idea is to store multiple items of the same type together. It allows the processing of a large amount of data in a relatively short period. It stores multiple data of the same type at one time. The first element of the array is indexed by a subscript of 0. There are different operations possible in Array like Searching, Sorting, Inserting, Traversing, Reversing, and Deleting.

Characteristics of an Array: 

An array has various different characteristics which is as follows:

• Arrays uses an index-based data structure which helps to identify each of the elements in an array easily using the index.
• If user want to store multiple values of same data type then array can be and utilized efficiently.
• Array can also handle complex data structure by storing data in two dimensional array.
• Array is also used to  Implement other data structures like Stacks, Queues, Heaps, Hash tables, etc.
• The search process in array can be done very easily.
• In array accessing an element is very easy by using the index number.

Applications of Array: 

Different applications of Array is as follow:

• Array is used in solving matrices problem
• Databases record are also implemented by array.
• It helps in implementing sorting algorithm.
• It is also used to  Implement other data structures like Stacks, Queues, Heaps, Hash tables, etc.
• Array can be used for CPU scheduling.
• Applied as lookup table in computer.
• Arrays can be used in speech processing, where every speech signal is an array.

Real Life Applications of Array: 

• Array is frequently used to store data for mathematic computations.
• It is used in image processing.
• It is also used in record management.
• Book pages is also real life example of array.
• It is used to ordering boxes also.

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Linked list: 

A linked list is a linear data structure, in which elements are not sorted at contiguous memory locations. The element in a linked list are linked using pointers as shown in the below image: 

Types of Linked List:

• Singly linked list
• Doubly linked list
• Circular linked list
• Doubly circular linked list

Characteristics of an Linked list: 

Linked list has various characteristics which is as follows:

• Linked list uses extra memory to store links.
• While initialization of linked list no need to know the size of the elements.
• Linked list used to implement stacks, queues, graph, etc.
• First node of the linked list is called as Head.
• Lat node  next always points to null.
• In linked list insertion and deletion is possible easily.
• Each node of linked list consists of pointer/link which is the address of the next node.
• Linked List can shrink or grow at any point of time easily.

Applications of Linked list: 

Different applications of Linked List is as follow:

• Linked lists are used to implement stacks, queues, graphs, etc.
• Linked list uses to perform arithmetic operations on long integers.
• It is used for representation of sparse matrices.
• It linked allocation of files.
• It helps in memory management.
• Manipulation of polynomials by storing constants in the node of linked list.

Real Life Applications of Linked list: 

• Linked list is used in Round robin scheduling, to keep track of the turn in multi-player game.
• It is used in image viewer. Previous and the next images are linked, hence can be accessed by next and previous button.
• In Music playlist songs are linked to previous and next song. 

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Stack: 

Stack is linear data structure that follows a particular order in which the operations are performed. The order may by LIFO(Last in first out) or FILO(First in last out). In this entering and retrieving data is possible from only one end. The entering and retrieving of data is also called push and pop operation in stack. There are different operations possible in Stack like reversing a stack using recursion, Sorting, Deleting the middle element of the stack etc. 

Characteristics of an Stack: 

Stack has various different characteristics which is as follows:

• Stack is used in many different algorithms like Tower of Hanoi, tree traversal, recursion etc.
• Stack is implemented through Array or Linked list.
• It follows Last In First Out operation i.e., element which inserted first will pop in last and vice versa.
• The insertion and deletion happens at one end i.e. from the top of the stack.
• In stack if allocated space for stack is full, and still if anyone attempt to add more elements will lead to stack overflow.

Applications of Stack: 

Different applications of Stack is as follow:

• Stack Data structure is used in evaluation and conversion of Arithmetic expression.
• Stack is used in Recursion.
• It is used for parenthesis Checker.
• While Reversing of String stack is also used.
• Stack is used in memory management.
• It is also used for processing of function call. 

Real Life Applications of Stack: 

• Real life example of a stack is the layer of eating plates arranged one above the another. When you remove a plate from the pile, you can take the plate on the top of the pile. But this is exactly the plate that was added most recently to the pile. If you want the plate at the bottom of the pile, you must remove all the plates on top of it is reach it. 
• Browsers uses stack data structure to keep track of previously visited sites.
• Call log in mobile also uses stack data structure. 

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Queue: 

Queue is a linear structure that follows a particular order in which the operations are performed. The order is First In First Out(FIFO) i.e., the data item stored first will be accessed first. In this entering and retrieving data is not done from only one end. An example of a queue is any queue of consumers for a resource where the consumer that came first is served first. Different operations are performed on Queue Reversing a Queue, Reversing a Queue using recursion, Reversing the first K elements of a Queue, etc. In Queue few basics operations involved are push, pop, peek, etc.

Characteristics of an Queue: 

Queue has various different characteristics which is as follows:

• Queue is a FIFO (First in First out) structure.
• To remove the last element of Queue, all the elements inserted before the new element in the queue must be removed.
• Queue is ordered list of elements of similar data types.

Applications of Queue: 

Different applications of Queue is as follow:

• Queue is used for handling website traffic.
• It helps to maintaining the playlist in media players.
• Queue are used in operating systems for handling interrupts.
• It helps in serving requests on a single shared resource, like a printer, CPU task scheduling etc.
• It is used in asynchronous transfer of data for eg. pipes, file IO, sockets.

Real Life Applications of Queue: 

• A real world example of queue is single lane one way road, where the vehicle enters first will exit first. 
• More real word example can be seen as queue at the ticket windows.
• Cashier in a store is also example of queue.
• People on escalator. 

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Tree:

The tree is non-linear and hierarchal data arranged in a tree-like structure. In the tree, the topmost node is called the root node. Each node contains some data, and data can be of any type. It consists of a central node, structural nodes, and sub-nodes which are connected via edges. Different tree data structures allow quicker and easier access to the data as it is a non-linear data structure. the tree has various terminologies like Node, Root, Edge, Height of the tree, Degree of a tree, etc. 

There are different types of Tree like 

Characteristics of an Tree: 

Tree has various different characteristics which is as follows:

• Tree is also known as Recursive data structure.
• In tree Height of root can be defined as the longest path from the root node to the leaf node.
• In tree one can also calculate the depth from the top to any node. The root node has 0 depth.

Applications of Tree: 

Different applications of Tree is as follow:

• Heap is a tree data structure which is implemented using arrays, and used to implement priority queues.
• B-Tree and B+ Tree is used to implement indexing in databases.
• Syntax Tree helps in scanning, parsing, generation of code and evaluation of arithmetic expressions in Compiler designs.
• K-D Tree is a space partitioning tree used to organize points in K dimensional space.
• Spanning trees used in routers in computer networks.

Real Life Applications of Tree: 

• In real life tree data structure helps in Game Development. 
• Also it helps in indexing of database. 
• Decision trees is efficient machine learning tool, commonly used in decision analysis. 
• Tree helps to understand the data using flow chart.
• Domain name server also uses tree data structure.
• The most common use case of tree in any social networking sites. 

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Graph:

Graph is a non-linear data structure that consists of nodes and edges. A graph consists of finite sets of vertices and sets of Edges that connect a pair of nodes. The graph is used to solve the most challenging and complex programming problems. The graph has different terminologies which are Path, Degree, Adjacent vertices, Connected components, etc.

Characteristics of Graph: 

Graph has various different characteristics which are as follows:

• Maximum distance from all vertices is considered as the eccentricity of that vertex.
• The vertex having minimum eccentricity is considered the central point of the graph.
• Minimum value of eccentricity from all vertices is considered as the radius of the connected graph.

Applications of Graph: 

Different applications of Graph are as follows:

• Graph is used to represent the flow of computation.
• It is used in modeling graphs.
• Operating system uses Resource Allocation Graph.
• Also used in the world wide web where the web pages represent the nodes.

Real-Life Applications of Graph: 

• One of the most real-world examples of a graph is Google map where cities are located as vertices and path is located as edges of the graph.
• Social Network is also one real-world example of graph where every person on the network is a node, and all the friendships on Instagram form the edges of the graph.
• Graph is also used to study molecules in physics and chemistry. 

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Conclusion

Although these are the most widely known and used data structures, there is some other form of data structures as well used in Computer Science, such as policy-based data structures, etc. But, no matter which data structure you choose, each one has its perks and disadvantages, without the knowledge of which, it can be very costly to choose the wrong type of data structure. So it is very important to understand the need for the situation, and then decide which kind of data structure suits best for the job.