January 21, 2022

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What is Data Structure: Types and Classifications

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Data is one of their most important tools for any business or organization looking to survive and rise in today’s highly competitive world. More information means more solutions and options for problems and obstacles.

This data comes with some heavy demands. For example, it must be organized and accessible. If a company can’t access the data and make it actionable, all the data in the world will not help it.

This dilemma leads us to the common question: What is a data structure? This article will discuss data structures and describe the various types, classifications, and how they are used. We will also explore concepts such as linear and nonlinear data structures. Interview questions about data structure will be covered, which is great for those applying for related positions.

Let’s get into the world of data structures and algorithms!

What’s Data Structure?

Data structures are specialized formats for organizing, retrieving, and storing data. There are many types of data structures available, both basic and more advanced. Each type is designed to organize data according to a specific purpose. Data structures allow users to quickly access the data they need and work with it most efficiently.

The data structure is a way to organize digital information. The data structure is an important component of Computer Science. It is used extensively in Artificial Intelligence, graphics, and operating systems.

Data Types and Their Relationship with Data Structures

The data structure can be described in three main data types.

Abstract:

An Abstract Data Type (or data type) is a mathematical representation of a data structure. It specifies the type and support for operations and the parameters. An Abstract Data Type describes the operation, but not its method. An Abstract Data Type can typically be implemented using many data structures.

Composite:

A composite data type has values made up of components (or values from other data types). An example of a composite data type is an array. int a[] = 1,2,3,4,5

Primitive:

Primitive data structures are data structures that store only one type of data. Non-primitive data structures can store data of multiple types. Primitive data structures include integer, character, and float.

Primitive data types include byte, short, int, long, float, double, boolean, and char.

These data types are the foundation of data structures. These data types inform the interpreter and the computer about the programmer’s plans for using the data. Data analysts can choose from a variety of data structure classifications. It is important to choose the right structure for you and your situation.

What are the Classifications of Data Structures?

There are many common data structures, including linked lists, queues, stacks, binary trees, and graphs, graphs, and hash tables. Based on how data is organized or aggregated, these data structures can be classified either as linear or nonlinear.

Let’s look at the classifications to help us understand data structures. There are three major data structure classifications. Each one consists of a pair of characteristics.

Linear and nonlinear

Linear data structures have data elements arranged linearly. Each element is attached to the next and previous adjacent. Data elements in a nonlinear structure are attached hierarchically.

Dynamic and Static:

Dynamic data structures allow for the modification of data structures during run-time. While static data structures have a fixed memory size, dynamic data structures can be randomly modified during run-time. This may make the structure more efficient in code complexity and memory.

Homogenous and Non-Homogenous:

Homogeneous structures can store only one type of data, such as numeric, integer, or character. Heterogeneous structures can store multiple types of data simultaneously.

The Different Data Structure Types

We have already covered data types and data structure classes. We will continue our walk through the various data structure elements by looking at different types of data structures.

Array:

An array is a collection of data items of the same type stored in contiguous memory locations. For example, an array of type “int” can store only integer elements. It cannot hold elements of other types like double, float, and char.

Graphs

A graph is a nonlinear data structure that consists of edges and nodes. Sometimes, the nodes are also called vertices. Edges are lines or arcs connecting any two nodes within the graph.

Hash tables

A hash table, also known as a “hash map” in computing, is a data structure that implements an abstract associative array data type. For example, this structure can map keys to value. A hash table uses the hash function, also known as a hash code, to compute an index into an array of buckets, or slots, where the desired value is found.

Linked list:

A linked list is a non-primitive data structure that has each element dynamically assigned and points to each other to establish a linear relationship. Nodes are elements of linked lists that contain two things: data and a pointer to the next node.

Stack:

A stack is an abstract data type that holds an ordered, linear sequence. A stack, unlike a queue, is an ordered, linear sequence of items. An example of this is a stack with plates. You can only take one plate from the top, and you cannot add another to the top.

Queue:

A Queue can be described as a linear structure that follows a specific order of operations. This order is called First in First Out (FIFO). A queue is a group of consumers waiting to be served for a resource. The key difference between queues and stacks is the removal.

Tree:

Trees are a nonlinear data structure. This contrasts to linear data structures like arrays, linked lists, stacks, stacks, and queues. A tree can be empty or have no nodes. It also has one root, zero, or one or several subtrees.

Trie:

A Trie is a sophisticated data structure, also known as a digital tree or prefix tree. It’s a tree that stores data in an organized and efficient manner. For example, to store strings, we use tries.

Now you know what data structure is. Are you interested in becoming a Data Scientist? Get certified today by AI Patasala’s Data Science Course in Hyderabad program.

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