An understanding of data structuring is vital for anyone who has to deal with huge amounts of data. Data structuring is the process that organizes data to make it more accessible and usable by software programs. There are many ways to organize data, but some of the most popular are dictionaries, arrays, and linked lists. Each has particular strengths, and it's important to know them all before choosing the one that is most suitable for your requirements.
Linear Data Structures
Based on the programming language, linear data structures can differ in their memory allocation and internal structure as well as the way basic operations (traversal, retrieval, insertion, deletion) are carried out. An excellent example of linear data structures is an array, which keeps its elements in multiple memory locations that are contiguous, where each element is accessible using an index starting at 0. These are suitable for applications that require sequential access to data and are useful for storing lists of information (like dates or addresses) and for performing mathematical calculations.
Non-Linear Data Structures
A tree is a non-linear structure that organizes data in the form of a hierarchy. Each record (or node) in a tree is linked to one or more successor records through a parent/child connection. Each child record could contain data or pointers that connect to other records within the tree. A family tree is an illustration of one. The main information is at the top, and then it branches out to grandchildren, children, etc.