Anyone who is dealing with huge amounts of data should have a good understanding of data structure. Data structuring is the process of organizing data in a way that it can be used and accessed by software programs. There are a myriad of ways to structure data, but some of the most popular are dictionaries, lists, and linked lists. Each of them has its own strengths and weaknesses, so it is crucial to comprehend each one before deciding which one is best suited to your specific needs.
Linear Data Structures
Based on the programming language being used, linear data structures may differ in their memory allocation, internal structure and how basic operations (traversal, retrieval, insertion, deletion) are performed. An array is a great example of linear data structures. It stores its elements in contiguous memory locations and every element can be accessed through an index that begins at zero. These are great for algorithms which require sequential data access. They can also be useful to store lists (like dates or address) and performing math computations.
Non-Linear Data Structures
A tree is an unlinear structure that arranges data in the form of a hierarchy. Each record (or node) in a tree is linked to one or more succeeding records by a parent/child relation. Each child record may contain m&a data room data or pointers that lead to other records within the tree. A good example of a tree is a family tree which has its principal piece of information at the top and then branches out into grandchildren, children and the like.
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