DSA Lesson 1 reviewer

Data

• “raw facts”
• information
• in a form of numbers, text, images, figures, or any other format
• structure or unstructured

Structure

(noun) - something arranged in a definite pattern of organization

Data Structures

• A specific way of organizing data in a specialized format on a computer so that the information can be organized, processed, stored, and retrieved quickly and effectively.

Data Structures

They are a means of handling information, rendering the data for easy use.

Data Structures

An integral part of computers used for the arrangement of data in memory.

Characteristics of Data Structures

• Linear or Non-Linear
• Static and Dynamic
• Time Complexity
• Correctness
• Space Complexity

• Linear or Non-Linear
• Static and Dynamic
• Time Complexity
• Correctness
• Space Complexity

Characteristics of Data Structures

Linear

data elements are arranged sequentially or linearly, where each element is attached to its previous and next adjacent elements. Examples of linear data structures are array, stack, queue, linked list, etc.

Non-Linear

data elements are not placed sequentially or linearly. In a non-linear data structure, we can’t traverse all the elements in a single run only. Examples of non-linear data structures are trees and graphs.

Static data structure

has a fixed memory size. It is easier to access the elements in a static data structure. An example of this data structure is an array.

Dynamic data structure

the size is not fixed. It can be randomly updated during the runtime which may be considered efficient concerning the memory (space) complexity of the code. Examples of this data structure are queue, stack, etc.

Homogenous data structure

consist of the same data element type, like element collections found in an array.

Non-Homogenous data structure

the data don’t have to be the same type, such as Linked List.

Data

is information optimized for processing and movement, facts and figures stored on computers.

Data Type

is a classification, or attribute of data which tells the compiler or interpreter how the programmer intends to use the data.

Data Type

is the form of a variable to which a value can be assigned. It defines that the particular variable will assign the values of the given data type only.

Data Type

It can hold value but not data. Therefore, it is dataless.

Data Type

The implementation of a data type is known as abstract implementation.

Data Structure

is a collection of different kinds of data. That entire data can be represented using an object and can be used throughout the program.

Data Structure

It can hold multiple types of data within a single object.

Data Structure

Data structure implementation is known as concrete implementation.

Advantages of Data Structures

• Good solution for storing data on framework.
• Easier for us to handle data.
• Aid us in efficiently storing data on circles so that we can recover the data.
• Critical for planning computations.
• The speed of program execution depends on the type of data structure used.
• Allow us to reuse data.
• Chart let us visualize, interact with, and model real-world challenges.
• Trees are data structures that let us see, carry out, and operate with hierarchical data sets.
• Data structures provide data deliberation so that the client does not have to be concerned with how the data is stored.
• When working with large data sets, the program's effectiveness is largely determined by the type of data structure used.
• Used in the database administration framework (DBMS)
• Serve a variety of functional objectives, such as dynamic memory distribution, process planning, record framework association, word reference, and so on.

Disadvantages of Data Structures

• The more the application or data structure involved in creating and maintaining the application, the greater the labor supply.
• Planning data structures without preparation is extremely difficult and may need sophisticated calculations and significant effort in addition to tests.
• Larger applications necessitate data structures within each other, just like the hub of a chart is made up of an exhibit or a rundown. As a result, maintenance is both puzzling and costly in such cases.

Needs of Data Structures

• Provides a way of organizing, managing, and storing data efficiently.
• Data items can be traversed easily.
• Provides efficiency, reusability and abstraction.
• It plays an important role in enhancing the performance of a program because the main function of the program is to store and retrieve the user’s data as fast as possible.

Importance of Data Structures

•Efficiency
•Flexibility
•Scalability