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Essential Data Structures: Must-Know Basics for Every Programmer

By Manas Kochar Category Data Structure Reading time 4.33 mins Published on Aug 23, 2023

Level up Your Coding Expertise With a Proven DSA Course Program!

Programmers often see difficulties in their career path due to stagnancy and lack of upskilling. Even though clearing the challenges at an entry level is easy but with seniority positions, these hardships get more critical. This demands constant learning of the latest concepts and removes the redundancies in their career.

Thus, advanced learning of data structures and algorithms to refine programming skills is useful for future career growth. As a promising candidate, you should be knowledgeable in basic data structures while appearing for technical interviews. You may gain knowledge of these data structures via an advanced DSA course. Learning DSA and its uses in programming is equally essential as coding.

Data structures knowledge helps you write efficient code required in industry applications. Hence, the expertise you gain from a data structures course will also help you look for better-paying jobs.

The top MNCs need a workforce with strong DSA knowledge. You can prepare for a job interview in such companies through a data structures and algorithms course.

List of the best data structures to master

1. Array

Arrays are among the more common data structures you can learn in a DSA course. They are typically containers of a fixed length that store several objects. The objects are of similar type and stored sequence-wise. There are elements of the same data types in an array called variables.

Arrays mainly act as containers for creating complex data structures and sorting algorithms.


  • Arrays help easily access the elements inside the container. It represents the elements using individual indexes to access them.
  • Arrays help provide effective memory usage as it keeps the elements within a single continuous storage space.
  • A single continuous storage space stores the elements, which makes searching and sorting inside an array easier.
  • Arrays are a great help for beginners to study data structures, as they're simple to understand. Performing tasks on an array seems to be quite easy and reliable.

2. Linked Lists

‘Linked lists’ consist of elements arranged sequentially and connected (linked) with each other. As a result, we can't access elements randomly. You must access them sequentially or in order. In this context, the starting point is termed as 'Head' & the ending point is called 'Tail.' A network consists of many elements, and each of the elements is denoted as a node. A network consists of a key and a pointer to the immediate next node of the list. Linked lists are of the following types:

Singly Linked List (Unidirectional): It makes moving forward through each element from head to tail possible.

Doubly Linked List (Bi-directional): It makes it possible to move forward and backward through each element.

Circular Linked List: It connects the head and tail of the liked list and forms a circle.


  • Linked lists are dynamic. It means they can shrink or grow in size at runtime. We can adjust its size accordingly to insert or delete elements.
  • Linked lists help easily insert or delete elements from memory. You can insert or delete elements from any position within the list.
  • The linked list allows efficient memory allocation. It allocates memory to only elements that are in use, saving memory space.
  • You can easily apply abstract data types like trees, stacks, and queues to a linked list.

3. Stacks

Stacks are a linear data structure quite familiar to arrays. Stacks implement LIFO order (Last in, First Out). It states the element placed last is taken out first. It arranges the elements above one another. You can learn more about stacks in data structures and algorithms courses.

You can add new elements (push) or delete the elements (pop) from the top. Stacks are helpful in recursion programming for applying function calls. They are also useful for parsing and evaluating mathematical functions.


  • Stacks provide effective data and memory management through the LIFO method.
  • Stacks help control memory allocation and deallocation.
  • Stacks are reliable and secure.

4. Queues

Queues are similar to stacks in the DSA course but follow the FIFO order (First in, First Out). We access the primary element that is first in the queue. At any point in time, we may add new elements (enqueue) at the back of a queue. And we can delete elements in front of the queue (dequeue).

Queues are helpful in multithreading. We can organize threads and implement priority queuing methods using queues. A data structure and algorithms course teaches the applications of queues and other data structures in detail.


  • Data queues are quick, efficient, and adaptable.
  • We can perform insertion and deletion operations easily using the FIFO method.
  • Queues can easily handle huge amounts of data. They can manage different data types.
  • Queues help us implement other data structures as well.

5. Tree

The tree is another common data structure that connects data, similar to linked lists. However, it arranges the data in a hierarchical structure. This data structure is not linear. Trees are complex data structures commonly used in AI (Artificial Intelligence) systems and complicated problem-solving processes.

The tree data structure is of different types, which are:

  • Binary search tree (BST)
  • AVL tree
  • N-ary tree
  • B tree, treap
  • Red-black tree
  • Splay tree

The binary search tree (BST) is a very popular tree data structure.


  • Due to the hierarchical structure, storing data in systems like databases and file management is convenient in a tree.
  • The BST helps reduce a search function's time complexity/ O(log(n)).
  • The tree offers flexibility as we can remove any node and easily attach it to another node.
  • There are many ways to traverse and arrange nodes in a tree, which is useful in several aspects of a problem.


DSA course plays an essential role in providing a basic understanding of software programming. However, improving your programming experience by implementing these data structures in live DSA projects is best. You can participate in a data structures course to gain knowledge of the same.

Various data structures and algorithms courses are available online, making it difficult for an individual to choose. But, you must enroll in the DSA and System Design Program with expert mentors and live assistance. They will help you practice and understand the various data structures and their real-world applications. You may also get IBM and Microsoft certifications to show your data structures expertise.