Anyone who works with large quantities of data should have a good understanding of data structure. Data structuring is a process which organizes data to make it accessible and usable by software programs. There are a myriad of ways to structure data, however the most commonly used are dictionaries, arrays, and linked lists. Each one has its own strengths and weaknesses, so it is essential to fully understand each one is the best for your particular requirements.

Linear Data Structures

Depending on the programming language being used, linear data structures can vary in their memory allocation, internal structure and how the basic operations (traversal, retrieval, deletion, insertion) are carried out. An array is a good illustration of a linear data structure. It stores its elements in memory locations that are contiguous and every element can be accessed https://gadgetnotify.com/understanding-the-functions-and-benefits-of-a-board-of-advisors/ via an index that begins at 0. They are ideal for algorithms that require sequential access to data. They are also useful to store lists (like dates or address) and for performing math calculations.

Non-Linear Data Structures

A non-linear data structure is a tree, which organizes data in a hierarchical fashion. Each record in the tree has a parent-child relationship that connects it to one or more records below. Each child record may contain information or references to other records within the tree. A family tree is an illustration of one. The primary information is at the top and then it extends to grandchildren, children, etc.