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Anyone who deals with large quantities of data should be aware of the structure of data. Data structuring is the process of organizing data so it can be accessed and used by software programs. There are a myriad of ways to structure data, but some of the most common are dictionaries, lists, and linked lists. Each has their own strengths, and it is important to know them all before selecting the one that best fits your needs.
Linear Data Structures
Based on the programming language being used, linear data structures can differ in their allocation of memory and internal structure as well as the way the basic operations (traversal, retrieval, insertion, deletion) are executed. A good example of linear data structures is an array that is able to store its elements in multiple memory locations that are contiguous, where each element is accessible through an index that begins at zero. They are efficient for algorithms that require sequential access to data. They are useful for storing lists of information (like dates or addresses) and for performing mathematical calculations.
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 successor records via a parent/child relationship. Each child record can contain data or points to other records in the tree. An excellent example of an example of a tree is a family tree that has its main element of data at the top and then branches out into grandchildren, children and so on.