Introduction to the Theory of Data Structures

 

Introduction to Data Structures

"Data" to refer to Computer Information, either transmitted or stored. However, there is data that exists in order types as well. Data can be numbers or texts written on a piece of paper, in the form of bits and bytes stored inside the memory of electronic devices, or facts stored within a person's mind. As the world started modernizing, this data became a significant aspect of everyone's day-to-day life, and various implementations allowed them to store it differently.

Data is a collection of facts and figures or a set of values or values of a specific format that refers to a single set of item values. The data items are then classified into sub-items, which is the group of items that are not known as the simple primary form of the item.

Let us consider an example where an employee name can be broken down into three sub-items: First, Middle, and Last. However, an ID assigned to an employee will generally be considered a single item

What is Data Structure?

Data Structure is a branch of Computer Science. The study of data structure allows us to understand the organization of data and the management of the data flow in order to increase the efficiency of any process or program. Data Structure is a particular way of storing and organizing data in the memory of the computer so that these data can easily be retrieved and efficiently utilized in the future when required. The data can be managed in various ways, like the logical or mathematical model for a specific organization of data is known as a data structure.

The scope of a particular data model depends on two factors:

1. First, it must be loaded enough into the structure to reflect the definite correlation of the data with a real-world object.
2. Second, the formation should be so straightforward that one can adapt to process the data efficiently whenever necessary.

Some examples of Data Structures are Arrays, Linked Lists, Stack, Queue, Trees, etc. Data Structures are widely used in almost every aspect of Computer Science, i.e., Compiler Design, Operating Systems, Graphics, Artificial Intelligence, and many more.

Data Structures are the main part of many Computer Science Algorithms as they allow the programmers to manage the data in an effective way. It plays a crucial role in improving the performance of a program or software, as the main objective of the software is to store and retrieve the user's data as fast as possible.

Basic Terminologies related to Data Structures

Data Structures are the building blocks of any software or program. Selecting the suitable data structure for a program is an extremely challenging task for a programmer.

The following are some fundamental terminologies used whenever the data structures are involved:

1. Data: We can define data as an elementary value or a collection of values. For example, the Employee's name and ID are the data related to the Employee.
2. Data Items: A Single unit of value is known as Data Item.
3. Group Items: Data Items that have subordinate data items are known as Group Items. For example, an employee's name can have a first, middle, and last name.
4. Elementary Items: Data Items that are unable to divide into sub-items are known as Elementary Items. For example, the ID of an Employee.
5. Entity and Attribute: A class of certain objects is represented by an Entity. It consists of different Attributes. Each Attribute symbolizes the specific property of that Entity. For example

Entities with similar attributes form an Entity Set. Each attribute of an entity set has a range of values, the set of all possible values that could be assigned to the specific attribute.

The term "information" is sometimes utilized for data with given attributes of meaningful or processed data.

1. Field: A single elementary unit of information symbolizing the Attribute of an Entity is known as Field.
2. Record: A collection of different data items are known as a Record. For example, if we talk about the employee entity, then its name, id, address, and job title can be grouped to form the record for the employee.
3. File: A collection of different Records of one entity type is known as a File. For example, if there are 100 employees, there will be 25 records in the related file containing data about each employee.

Understanding the Need for Data Structures

As applications are becoming more complex and the amount of data is increasing every day, which may lead to problems with data searching, processing speed, multiple requests handling, and many more. Data Structures support different methods to organize, manage, and store data efficiently. With the help of Data Structures, we can easily traverse the data items. Data Structures provide Efficiency, Reusability, and Abstraction.