Important Points

Key Points to keep in mind

Important Points

Before introducing data structures we should understand that computers do store, retrieve, and process a large amount of data.
If the data is stored in a well-organized way on storage media and in the computer's memory then it can be accessed quickly for processing that further reduces the latency and the user is provided a fast response.
Data structure introduction refers to a scheme for organizing data, or in other words, a data structure is an arrangement of data in a computer's memory in such a way that it could make the data quickly available to the processor for required calculations.
A data structure should be seen as a logical concept that must address two fundamental concerns.
First, how the data will be stored, and second, what operations will be performed on it?
As data structure is a scheme for data organization so the functional definition of a data structure should be independent of its implementation.
The functional definition of a data structure is known as ADT (Abstract Data Type) which is independent of implementation.
The implementation part is left on developers who decide which technology better suits their project needs.
For example, a stack ADT is a structure that supports operations such as push and pop. A stack can be implemented in a number of ways, for example using an array or using a linked list.
Along with data structures introduction, in real life, problem-solving is done with help of data structures and algorithms.
An algorithm is a step-by-step process to solve a problem. In programming, algorithms are implemented in form of methods or functions, or routines.
To get a problem solved we not only want an algorithm but also an efficient algorithm.
One criterion of efficiency is the time taken by the algorithm, another could be the memory it takes at run time.
Sometimes, we can have more than one algorithm for the same problem to process a data structure, and we have to choose the best one among available algorithms. This is done by algorithm analysis. The best algorithm is the one that has a fine balance between the time taken and memory consumption.

But, as we know the best exists rarely, and we generally give more priority to the time taken by the algorithm rather than the memory it consumes.

Also, as memory is getting cheaper and computers have more memory today than in previous time, therefore, run time analysis becomes more significant than memory.

The analysis of algorithms is an entirely separate topic and we will discuss that separately.

Introduction to Basic Data Structures and Algorithms

Classification of Data Structures

Arrays

Linked List

Stack

Queue

Tree

Heap

Dictionary

Hash Table

Graph