Anyone who is dealing with large quantities of data should be aware of the structure of data. Data structuring is the process of arranging data in order to make it easier for it to be used and accessed by software programs. There are many ways of structuring data, but the most common ones are linked lists, arrays and dictionary. Each has particular strengths, and it is important to know all of them before choosing the one that best fits your requirements.
Linear Data Structures
Linear data structures differ based on the programming languages they are written in. They can differ in the allocation of memory as well as internal structure and the way that basic operations like traversal of data, retrieval, insert, and deletion are performed. An excellent example of linear data structures is an array that stores its elements at the same memory location, where each element is accessible by using an index that starts at zero. They are useful for algorithms that require sequential access to data and are great for storing lists of information (like dates or addresses) and performing mathematical computations.
Non-Linear Data Structures
A tree is a non-linear structure used to organize data in the form of a hierarchy. Each record in a tree has a parent-child relationship that connects it to one or more records below. Each child’s record can contain information or references to other records within the tree. An excellent example of an example of a tree is a family tree which has its primary piece of information at the top, and then branches out into grandchildren, children, etc.