Data Structures is one of the core concepts of Computer Science and many other technologies and advanced concepts implement them in some way. Knowing Data Structures are essential to advancing understanding of Computer Science in general and learning them is one the best investments made in case of pursuing a career in Computer Science. So, what are Data Structures and why are they important?
To begin with, Data Structures is a way of organizing data in a way that enables various operations to be performed more efficiently, for example insertion, deleting, updating, searching, etc. As the amount of data is growing constantly and exponentially, handling the data effectively is vital. Here is the case when Data Structures come into play. Data Structures give various options to take depending on the arisen case. A case maybe to implement efficient searching, deleting, storing big amounts of data, or all the mentioned operations simultaneously. Hence, choosing the right data structure may give big advantages in terms of time and memory usage.
Data Structures basically consist of two main types:
Linear Data Structures — LinkedList, Array, Stack, Queue
Non-linear Data Structures — Tree, Binary Tree, Heap, Graph
Linear Data Structures are data structures that are formed linearly and linked to each other. Arrays, Stacks and Queues are common examples of Linear Data Structures.
Non-linear Data Structures are mainly tree-based data structures. As the name says, these data structures have a structure similar to a tree. On each level there is a node that may or may not have child nodes. Trees are one of the fundamental data types and commonly applied since they provide efficient and fast operations of searching, deleting and insertion.
This is a short guide to Data Structures and in the next series of posts most of the Data Structures will be discussed, starting from the basic ones to more advanced.