Web Developers working with huge amounts of data encounter many challenges related to extracting, storing, retrieving, and manipulating the data according to the requirements. The basics of data structures and algorithms are concepts of computer science that help developers deal with these challenges most efficiently. Therefore, developers need to be proficient with concepts such as data structures and algorithms while dealing with any kind of data.
Also, knowing data structures and algorithms helps the developers to crack interviews related to the jobs of Data engineers, Data analysts, or Data scientists.
The data structures refer to a unique format for storing, processing and retrieving data. The data used by individuals and organizations must be stored in a specified format, enabling the data users to access and use the information easily. It is crucial to understand these data structures to design appropriate software solutions for problem-solving.
Types of Data Structures
Data structures in computer science are broadly classified into two different categories
- Linear Data structures
- Non – Linear Data structures
A. Linear Data Structures
As the name indicates, the elements are arranged linearly, in a sequential manner that comes one after another, thus, making it easier to understand and implement.
This structure is only suitable for less complex data sets. If one has to deal with large and complex data sets, linear data structures may not be suitable.
1. Stack Data structure – Stack data structure is a linear structure that follows the LIFO Last in first out or FILO first in last out principle.
For instance, the stack of plates stored in a restaurant’s kitchen. The customers are served food by removing the plate which was placed last in the stack.
2. Array Data Structure – An array is a group of elements stored one after another, next to each other. The structure collects the same type of data to be stored sequentially.
3. Queue Data Structure – Queue data structure is a linear data structure that follows the FIFO First in, first out principle.
As the name indicates, it is similar to a queue of people standing to get a movie ticket, wherein the first person in the queue gets the ticket first.
4. Linked List Data Structure – Information is stored as nodes in a linked list data structure. Every other node in the list comprises 2 different types of information - the data and the address of the next node.
B. Non – linear Data structure
Unlike linear data structure, in non–linear data structures, elements are arranged in a non – sequential manner.
There are two types of non–linear data structures
1. Graph – data structure
There are different nodes called vertexes on a graph data structure. These nodes are connected to the other vertices through edges.
2. Trees data structure
The data elements are connected non-sequentially, wherein elements are connected via different nodes arranged at different levels.
Importance of Data Structures
- Data structures help in systematically storing and retrieving data
- It helps in efficient searching of the relevant information
- It also helps organize complex databases into the simplest, easy-to-access, and utilized formats.
- Data structures enable better problem solving
- They help in providing a means to manage complex and heavy data sets efficiently.
Algorithms in computer science are certain sets of rules or canons to solve a particular problem. Certain inputs are given to produce a desired output.
Algorithms are in every aspect of life. We humans, too, are programmed in a specific manner. For example, getting up daily, completing household chores, etc.
Similarly, computers have certain algorithms to perform a particular task.
For example, an algorithm to subtract two different numbers.
Take two numbers, for instance, 10 and 6
Subtract both the numbers using the operator “-, “10 – 6
The inputs display the result, 10 – 6 = 4.
Following are some categories of algorithms in computer science.
- Search is an algorithm to search any data or information item in the data structure.
- Sort – Algorithm to sort out the data in a particular way.
- Insert – Algorithm to insert a specific item in the data structure.
- Update – Algorithm to update the existing data structure.
- Delete – algorithms to delete an item or certain sets of information in the data structure.
Advantages of algorithms
- They are easy to understand.
- Provides a step-by-step input for problem-solving.
- Writing an algorithm is too time-consuming.
- Certain elements, such as branching or looping, are difficult to showcase in an algorithm.
Data structures and algorithms are crucial to ensure the program performs better and faster. The developers must be well aware of the data structures and various algorithms to develop computing programs that align with the client's needs and requirements, thereby executing tasks as systematically and accurately as possible.
Due to the increasing usage of artificial intelligence in computer science, the demand for data engineers, data analysts, and scientists has also been booming at an increased pace; thus, a solid understanding of data structures and algorithms enables developers to develop optimum solutions for real-life problems. These concepts are the basics of any technical interview; thus, they are asked in different coding tests and assessments.
What is a data structure?
Data structures are the formats in which manner specific data sets should be stored for further processing and analysis.
What does the “search” algorithm do?
The search algorithm is used to find any data or information present in the datasheet.
Why should I learn about data structures and algorithms?
Data structures and algorithms are the fundamentals of any coding program. You need knowledge about data structures and algorithms for rewarding careers such as data engineer, software developer, database administrator, etc.
Where can I learn about data structures and algorithms?
Many tutorials and books are available easily for learning about data structures and algorithms. One such platform is Masai, a higher education platform that provides 100% distance online learning sessions for computer science and software development courses.
How much salary can I expect after completing the DSA data structure and algorithms course?
The salary varies from organization to organization ranging between 0.8 LPA to 12.5 LPA. The average salary after completing the DSA course is about 2.5 LPA.