What is Data Structure: How It Works and Functions

Data structures are basically different ways to store and organize data on your computer. There are different types of data structures, some are basic and some are advanced that are used in almost every program that has been developed.

Types of Data Structure

•  Linear Data Structures: 
  

In Linear Data Structures elements are arranged in a sequence one after the other, examples of Linear Data Structures are array, stack, queue, linked list, etc.

Now, within the Linear data, there are Static data structures and Dynamic Data Structures. In Static data structures the memory is fixed and it is easier to access data in the Static data structures.

Example of a Static data structure is an array.

In the Dynamic Data Structures, the memory is not fixed and the Dynamic Data structure can be updated randomly during the runtime. Examples of a Dynamic data structure are stack, queue etc.

In Non-linear Data Structures, the elements of a program are not placed sequentially, In Non-linear data structures we can’t go through all the elements in a single run only.

Examples of Non-linear data structures are trees and Graphs.

For a simple program Linear Data Structures are good and easy to implement but for a complex program Non-Linear Data Structures are required.

Some operations we can do on Data Structures:

• Searching: We can search for any element in a data structure.
• Sorting: We can sort the elements of a data structure either in an ascending or descending order.
• Insertion: We can also insert the new element in a data structure.
• Updation: We can also update the element, i.e., we can replace the element with another element.
• Deletion: We can also perform the delete operation to remove the element from the data structure.

1. Array Data Structure:

In an array, elements in memory are arranged in continuous memory. All the elements of an array are of the same type. And, the type of elements that can be stored in the form of arrays is determined by the programming language.

2. Stack Data Structure:

In stack data structure, elements are stored in a way that the last element stored in a stack will be removed first.

3. Queue Data Structure:

A queue is defined as a linear data structure that is open at both ends and the operations are performed in First In and First Out (FIFO) order.

We define a queue to be a list in which additions are made at one end and subtraction to the list on the other end.

4. Linked List Data Structure:

In linked list data structure, data elements are connected through a series of nodes. And, each node contains the data items and address to the next node.

NON - LINEAR DATA STRUCTURES:

1. Graph Data Structure: 

A graph consists of vertices and edges. The vertices are sometimes also referred to as nodes and the edges are arcs that connect two nodes in the graph. 

2. Tree Data Structure:

Similar to graph data structure, a tree is also a collection of vertices and edges. But in tree data structure, there can only be one edge between two vertices.

WHY DATA STRUCTURES ARE IMPORTANT?

Knowledge about data structures can help you understand the working of each data structure and based on that knowledge you can select the right data structures for your project.

This will help you write memory and time efficient code.

Conclusion

Learning about data structures is very important for every CS student and every other professional who is working with the latest technologies around. And learning data structures from Industry experts and doing project based learning is also important to crack the interviews conducted by the world’s best MNCs, and Mappen provides a full fledged course on Data Structures which helps students master Data structures.

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Frequently Asked Questions(FAQs) 

Q. Why are data structures important?

Data structures are important because they provide a way to store and manipulate large amounts of data efficiently. They are used in many areas of computer science, including databases, operating systems, and programming languages.

Q. What are the common types of data structures?

Some common types of data structures include arrays, linked lists, stacks, queues, trees, and graphs.

Q. What is space complexity?

Space complexity is a measure of how much memory an algorithm uses as a function of the input size. It is usually expressed in terms of big O notation, which gives an upper bound on the growth rate of the algorithm.

Q. What is a recursive data structure?

A recursive data structure is a data structure that can be defined in terms of itself. For example, a tree can be defined as a node with a value and a list of child trees, where each child tree is also a tree.

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