A thorough understanding of data structuring is vital to anyone who deals with huge amounts of data. Data structuring is the process of arranging data so it can be accessed and utilized by software programs. There are a myriad of ways of structuring data however the most popular ones are linked lists, arrays, and dictionary. Each has its own strengths, and it’s important to know them all before deciding on the one that is most suitable for your requirements.

Linear Data Structures

Depending on the programming language being used, linear data structures can vary in their allocation of memory, internal structure and how fundamental operations (traversal retrieval, insertion, deletion) are carried out. An array is an excellent illustration of linear data structures. It stores its elements in contiguous memory locations and every element can be accessed via an index that begins at zero. They are useful for algorithms that require access to data in a sequential fashion and are useful to store lists of information (like dates or addresses) and performing mathematical computations.

Non-Linear Data Structures

A tree is a non-linear structure that organizes data in a hierarchy. Each record (or node) in a tree is linked to one or more successor records through a parent/child connection. Each child’s record may contain information or pointers that connect to other records in the tree. An excellent example of one is a family tree, which has its principal piece of data at the top and then branches out into children, grandchildren and the like.

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