Today, data is one of the most common terms that everyone uses several times in their daily life. It doesn’t matter which industry you are in; data is a common but powerful tool.
For any business of any scale or size, data is an essential thing that plays a vital role in deciding future strategies and individual roles in an organization. The business market has become quite competitive and challenging today, and if you are not doing data evaluation regularly, you might fall behind from the competition. The more organized and insightful your data is, the more chances you have to take sound and profitable decisions.
It is not easy to leverage data, as there are several parameters involved. You need to go through heaps of data, organize it, and transform it into a usable format before anything can be done. This is where data structures come in.
In this blog, we have discussed data structures in detail. Read it and get a clear picture of what data structures are, as well as their types, how to classify them, and their applications in today’s world.
What is a Data Structure?
A data structure is a method to organize data in a specialized form. It assists in organizing, processing, and storing data effectively. When it comes to handling and organizing data, a data structure is the best way to carry out things. Each application or piece of software usually has two components: algorithms and data.
Data is all about useful information, while algorithms are simply the instructions you follow while transforming data into programming. Data structures are an essential part used in arranging data. They have different characteristics, applications, and types that determine how they can be used.
How Data Structures Work
As mentioned above, data structures are organizational tools that help data pros to manage internet services efficiently. The data structure also assists in updating various online servers and network issues in the best possible way.
It filters and sorts large quantity data, and three essential parts incorporate it into the operational data structure.
- Memory address
- Pointer
- Procedure
These structural data parts are highly essential as their use and how we leverage these in a website or given database determines what type of data structure would work the best for the database.
Types of Data Structures
A data structure is an important part of our daily lives; we use it differently throughout our day. Various data structures help users solve many logical and mathematical questions daily. The data structure works best if you want to organize and process large data in a short period of time. Data structure varies according to its use and applications, which is why we will discuss different data structures that we can use in multiple situations. So, read on and look at how the data structure is classified.
Basically, there are two types of data structure.
- Linear data structure
- Non-linear data structure
1. Linear Data Structure
When we talk about linear data structure, the elements are arranged alternately in a sequence of one after the other. When elements are arranged in a particular order, it becomes easy to use them effectively by implementing them in the right way. But if you are looking to arrange complex data, a linear data structure is not the right choice because it has some operational complexities, which limits its use.
Linear data structures are sub-divided into:
a. Array Data Structure
An array data structure is one in which the elements are arranged in continuous memory. The elements are the same in an array data structure, and the programming language determines the type of stored elements in an array form.
b. Stack Data Structure
When it comes to a stack data structure, the LIFO principle is used to store elements, which means the last element will be removed first in a stack.
c. Queue Data Structure
The queue data structure is the opposite of the stack data structure. It uses the FIFO principle and removes the initial or first element in the queue.
d. Linked List Data Structure
When we talk about linked list data structure, it deals with the connection of data elements through a node series in which each node has a data item it addresses to the adjacent node.
2. Non-Linear Data Structures
Non-linear data structures are those in which elements are not arranged in sequence.
In non-linear data structures, the elements are arranged in a hierarchical manner which means that each element is connected to one or sometimes more elements, or elements are randomly arranged without a linear structure. This type of data structure is divided into two types.
a. Graph Data Structure
This type of non-linear data structure is defined as a data structure with finite vertices and edges. The edges help in the connection of vertices. The vertices help store data elements, and when we talk about the edges, it represents the relationship between the vertices.
b. Trees Data Structure
It comprises several nodes in a hierarchical order. The tree data structure consists of a root node with its various sub-nodes. These sub-nodes are usually referred to as child nodes and are present at the next level.
So, these are some of the types of data structures that are classified according to the arrangement of stored elements.
Applications of Data Structures
When we talk about data structure applications, we cannot define them generally as all the data structure types work differently because of their different element storage function. Let’s have a look at the applications of data structures precisely to understand them better.
Applications of Array Data Structures
- They are a building block used widely to build other data structures like vectors, matrices, tables, and more.
- They also work the best in sorting different algorithms such as merge sort, bubble sort, insertions sort, and quick sort.
- One of the best applications of array data structures is its wide model collection in computer programming.
Applications of Stack Data Structures
- It is easy to do backtracking with a stack data structure.
- It helps in the removal of recursion and the evaluation of expressions.
- Tree and graph traversal.
- You can also convert between expressions.
Applications of Queue Data Structures
FIFO storage of queue data structure helps in the following:
- It helps manage resource sharing, like scheduling computer processing units and disk scheduling.
- It is also a way out when data is sent and received between two processors, not necessarily at the same rate.
Applications of Linked List Data Structures
- The best application of linked list data structure is for dynamic memory allocation.
- It assists in implementing other data structures like stacks, trees, queues, graphs, and more.
- The doubly linked list is used in navigation systems to implement Undo and Redo functions.
- It manipulates polynomials.
- It is also used in representing sparse matrices.
Applications of Graph Data Structures
- The best application of graph data structure is to find the shortest path and social networks.
- It is widely used in transportation networks like Google Maps.
- It helps in representing a molecular structure and also helps with airline networks.
Applications of Tree Data Structures
- The best application of tree data structure is its use in bridges and routers with the help of spanning trees and shortest path trees.
- The Binary Search Trees search an element in a set quickly.
- There is a kind of tree called a Heap which helps in heap sorting.
- There is a modified version of a tree called Tires, which helps to store router information in routers.
Why is Data Structure Important?
As we live in the most advanced world with the most advanced technology, an understanding of data structure is the need of time. Today, various applications are available that have effectively made their place in the tech world. The complexity of the data structure and the amount of data compels us to understand data structure.
Without the correct data structure knowledge, dealing with many problems or things that cause complexities is impossible. You cannot find solutions for problems, and it will become difficult to find solutions affecting the processing speed.
It will be difficult to search data, and you will be unable to handle multiple requests if you don’t have the proper knowledge of data structure.
A data structure is more important than we think because it provides an easy way to organize and manage data efficiently. With the correct knowledge of data structure, you can transverse data items and store data easily.
Learning data structure will not just benefit you in sorting out things easily; it also plays an important role if you want to be the best programmer. With the correct data structure knowledge, it won’t be that difficult for you to do coding, which is said to be reliable and efficient. Data structure helps programmers to solve problems easily in no time and gives the best results.
Conclusion
So, this is all about the data structure, classification, and applications. We hope that you have much idea of how data structure plays an important role in the tech world and that programmers with the correct knowledge of data structure can do wonders in any field.
