Data Structure Introduction

The basic building block of DATA STRUCTURE are "data" and "information". So, before discussing data structure, we need to understand what is data and some ground facts about data structure.


many people use the terms "data" and "information" as synonyms but these two terms actually convey very distinct concepts. 

• "data" is defined as a body of facts or figures, which have been gathered systematically for one or more specific purposes
• data can exist in the forms of
• linguistic expressions (e.g. name, age, address, date, ownership)
• symbolic expressions (e.g. traffic signs)
• mathematical expressions (e.g. E = mc²)
• signals (e.g. electromagnetic waves)

• "information" is defined as data which have been processed into a form that is meaningful to a recipient and is of perceived value in current or prospective decision making
• although data are ingredients of information, not all data make useful information
• data not properly collected and organized are a burden rather than an asset to an information user
• data that make useful information for one person may not be useful to another person
• information is only useful to its recipients when it is
• relevant (to its intended purposes and with appropriate level of required detail)
• reliable, accurate and verifiable (by independent means)
• up-to-date and timely (depending on purposes)
• complete (in terms of attribute, spatial and temporal coverage)
• intelligible (i.e. comprehensible by its recipients)
• consistent (with other sources of information)
• convenient/easy to handle and adequately protected

DATA STRUCTURE DEFINITION :-

            Data structure is a collection of data elements whose organization is characterized by accessing functions that are used to store and retrieve individual data elements.

OR

               The logical or mathematical model of a particular organization of data is called data structure.

The two important goals of data structures are first to identify the representation of abstract entities and then to identify the operations, which can be performed with them. The operations help us to determine the class of problems, which can be solved with these entities. The proper construction of a program is influenced by the choice of data structure, which is used. A data structure is a systematic way of organizing and accessing data, and an algorithm is a step- by-step procedure for performing some task in a little amount of time. 

Depending on the organization of the elements, data structures are classified into two types:

• Linear Data Structure: Elements are accessed in a sequential order but it is not compulsory to store all elements sequentially (say, Linked Lists). Examples are Linked Lists, Stacks and Queues. 
• Non-Linear Data Structure: Elements of this data structure are stored/accessed in a non-linear order. Examples are Trees and Graphs.

To simplify the process of solving the problems, we generally combine the data structures along with their operations and are called Abstract Data Types (ADTs). An ADT consists of two parts:

• Declaration of data
• Declaration of operations