by Jasleen Chhabra | Updated on 11 November 2024

What is Data?

Data is a collection of facts, figures, and statistics that are collected for reference, analysis, or decision-making. Data can be anything from numbers and words to images, videos, and sounds.

Data Sets

A data set is a collection of related data. For example, a data set might include information about all the students in a school, such as their names, ages, grades, and addresses.

Entity

An entity is an object that exists and is distinguishable from other objects. In the context of a database, an entity could be a person, place, thing, or event that is represented by a set of data. For instance, in a school's database, a student would be an entity.

Table

A table is a collection of data organized in rows and columns. Each row represents a single record, and each column represents a specific attribute of that record. For example, a table of students might have columns for student ID, name, age, and grade.

What is a Data Structure?

A data structure is a method of organizing and storing data in memory to ensure efficient usage. Unlike programming languages such as C, C++, or Java, data structures are a collection of algorithms that can be utilized within any programming language to manage data in memory. Various algorithms, known as abstract data types (ADTs), are employed to define the rules for structuring data.

Types of Data Structures

Data structures are broadly classified into two categories:

1. Primitive Data Structures: These include basic data types like int, char, float, double, and pointers, which hold a single value.
2. Non-Primitive Data Structures: These are further divided into:
   • Linear Data Structures: Data is arranged sequentially. Examples include arrays, linked lists, stacks, and queues.
   • Non-Linear Data Structures: Data is connected in a hierarchical or network manner, such as trees and graphs.

Data structures can also be categorized as static or dynamic:

• Static Data Structures: Size is determined at compile time, making the maximum size fixed.
• Dynamic Data Structures: Size is determined at runtime, allowing flexibility in maximum size.

Major Operations on Data Structures

Several common operations can be performed on data structures:

• Searching: Locating an element within the data structure.
• Sorting: Arranging elements in ascending or descending order.
• Insertion: Adding new elements to the data structure.
• Updation: Modifying existing elements within the data structure.
• Deletion: Removing elements from the data structure.

Choosing the Right Data Structure

Selecting the appropriate data structure depends on the efficiency in terms of both time and space. For instance, a stack can be implemented using arrays or linked lists. Arrays might offer time efficiency, while linked lists might provide space efficiency. The choice of data structure should align with the specific requirements of the application.

Advantages of Data Structures

Data structures offer several benefits:

• Efficiency: Proper selection of data structures enhances the program's efficiency in terms of time and space.
• Reusability: Data structures can be reused across multiple programs, enhancing their utility.
• Abstraction: Data structures defined by ADTs offer a level of abstraction, allowing clients to use them without needing to understand the internal implementation details.

Understanding these basic concepts of data structures is crucial for any aspiring programmer or data scientist. They form the backbone of efficient algorithm design and software development, enabling the creation of robust and high-performance applications.

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