A good understanding of data structure is crucial for anyone who has to deal with large quantities of data. Data structuring is the process of arranging data so it can be accessed and used by software programs. There are many ways to structure data, however some of the most common are dictionaries, arrays, and linked lists. Each has its own strengths and weaknesses, therefore it is important to understand each one to use for your particular requirements.
Linear Data Structures
Linear data structures differ based on the programming language they are written in. They may differ in the allocation of memory and internal structure, as well as the way basic operations such as traversal, retrieval, insertion and deletion are handled. An array is an excellent example of a linear structure. It stores its elements in memory locations that are contiguous. every element can be accessed via an index that starts at 0. These are suitable for applications that require sequential access to data. They can be 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 into the form of a hierarchy. Each record in the tree has a parent-child relationship that connects it m&a data room to one or more records below. Each child record can contain information or pointers that connect to other records within the tree. A family tree is an illustration of one. The primary information is at the top, and then it branches out to children, grandchildren, etc.