What Are Data Structures and Algorithms?

 What Are Data Structures and Algorithms?

Are you interested in a career in the IT industry and want to become a successful software engineer? If yes, then you must have knowledge of data structures and algorithms (called DSA in short). Because today it has become an essential part of every programming language and every software uses it. Apart from software industry, they are also used in banking and finance health care service sector, entertainment and life sciences and top companies like ISRO, Google, Amazon, IBM and Infosys also use data structures and algorithms. That is, if mastery is achieved on these tools, then bright chances of getting a job in such top companies can also be made. In such a situation, you must also know about data structures and algorithms. And it should be learned about learning. However, learning is a bit tough, so most computer science students prefer to skip it. But maybe you will change your mind after knowing its importance, so read this informative article completely.

Why is it so important to learn data structures and algorithms?

It is important to learn them properly so that you can understand the organizing principles of web development and programming work. This DSA is a fundamental coding concept. DSA skills can shine your portfolio as a programmer. Startups prefer candidates having strong knowledge. DSA is often used in research and through this you can learn to solve many problems. It is not limited to any programming language, but you can use it in any programming language. That is, DSA has a lot of importance, so let us know about it with a little more encouragement. Data structures and algorithm is a computer science branch that deals with machine efficient and optimized computer programs. Data structure term refers to data storage and organization, then algorithm refers to step by step procedure done for desired outcome. These are two different tools which combine and give computer programmers the facility to build a computer program of their choice. Some common data structures and algorithms are linked lists, stacks, queues, sets, maps, hash tables, and search trees. 

Now to understand these two tools clearly, let us know about them one by one:

░Data Structure░

Data structure is a specialized format to store and organize data in computer science. This data structure is a key component of computer science and it is used in artificial intelligence, operating systems and graphics etc. Most of the data structures are inspired from real life only. It is just like you should keep the clothes in the wardrobe in such a systematic manner that next time when you need a specific cloth, you can easily remove it, that is, you should arrange your clothes which are a kind of data in such a structure in which If needed, you can easily remove a specific cloth without any haste. Just this type of organized structure is data structure, the need of which has increased a lot now because applications are becoming complex and data rich, due to which applications have to face this common problem which includes data search, processor speed and multiple requests. And the way to solve all these problems is data structures because data can be organized in such a way that there is no need to search all the items at the same time and easily required data can be searched.

Primitive and non-primitive data structures are the two forms of data structures.

1. Primitive data structures:

There are primitive data types which include INT chart flow, double pointer data structures which can hold a single value.

2. Non primitive data structure:

There are two types of non primitive data structure linear and non linear data structure, when the arrangement of data is done in a sequential manner then it is called linear data structure. Such data structures include array, linked list, stack and queue. In such data structures, in a linear form, an element is connected to only one other element. And when one element is connected to more than one element then it is called non linear data structure. Like trees and graphs in which elements are arranged in a random manner.

Apart from these, data structures are also classified into static and dynamic data structures. In static, size is allocated at compile time, due to which the maximum size of the data is fixed, while in dynamic, size is allocated at run time, due to which the maximum size is flexible.

Common operations of data structures include-

• Searching: That is, we can search any element in the data structure.
• Sorting: The elements of the data structure can be shortened in ascending and descending order.
• Insertion: any new element insert can also be done in the data structure.
• Update: The element can also be updated i.e. You can swap out one piece for another.
• Deletion: Deletion means any element from the data structure can also be deleted.

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░Algorithms░

Algorithm The set of steps that are used to complete a certain task or to get the desired output is called an algorithm. It is like building blogs for programming which allows smart phones, computers and websites to function smoothly and take decisions. As it happens in GPS, that is, when you search for a location, GPS checks multiple available routes using an algorithm, and computers also use the algorithm for fast calculation. But not every procedure can be an algorithm and for an algorithm to work it must have this characteristic. Algorithm should be clear and unambiguous. An algorithm must have 0 or well defined inputs, the algorithm must have one or more well defined outputs and it must also match the desired output. Algorithm should terminate after a limited number of steps and it should have step by step directions which should be independent of any programming code and as we know that algorithm is such a step by step procedure to solve a problem which is limited  step. These steps include branching and repetition and depend on the problem for which the algorithm has been developed. All the steps of Algorithm should be written in human understandable language which does not depend on any programming language.

Any programming language can be chosen to implement the algorithm and pseudo code and flowchart are popular bases for representing the algorithm.

Some common categories of algorithms are search, shortening, graph and tree traversal, dynamic programming and hashing and regex and if you know some important categories of algorithms from data structure point of view then they are-

Search: A search algorithm for a data structure item

Short: Algorithm to shot items in certain order in data structure

Insert: Data structure item insertion algorithm

Update: Algorithm to update existing item in data structure

Delete: Algorithm to delete existing item.

If after taking this information about data structures and algorithms, you want to learn them, then you can start learning it through books, tutorials or lectures and can learn them through practice.