Data Objects and Data Types:Data Structures allow basic operations such as traversing, inserting, deleting, updating, searching and sorting. These operations are backed up by data objects and data types concepts. You can compare data structure to the data definition, while an object is its implementation.
Data Objects : contain the actual information and can access the methods or information stored in the data structure. They can store, retrieve, or process the information in your program. Unless you garbage collect them at the end of the program, they continue to persist in the memory.
Data Types : define what type of data is stored in the variable. We can categorize them into primitive data types such as boolean, integer, float or character and complex data types such as an integer array.
Real-world applications:All complex solutions rely on Data Structures. We use them in many scenarios as described below:
This process uses heap and stack concepts for storing and retrieving data from memory.
Business operations: Complexity of data makes it even more complex to represent them in a more meaningful way. Graphs, for example, can help resolve the issue giving more clarity and meaning to the data.
Whether it is building operating systems, or database management, Data Structures are helpful. Most modern technologies such as artificial intelligence, data analytics, or numerical analysis also need Data Structures for proper storage and representation.
Types of Data Structures:We can categorize Data Structures into:
Linear Data Structures:
Some data structures are sequentially stored for easy storage and management. Files, queues, lists, arrays and stack are some examples of linear data structures. Files can be stored and accessed sequentially. Arrays, linked lists, queues or stacks are accessed directly using the address pointers.Below are some representation of arrays, stacks, queues, and linked lists.
Queues and Stack:
Non-Linear Data Structures:
When information doesn’t follow any specific storage pattern, but they are still related, non-linear data structures are used to manage them. Non-linear data structures are complicated and not easy to manage.
However, many real-time applications are complex and need non-linear data structures like trees and graphs.
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