Elementary Data Organizations

Basic Terminologies: Elementary Data Organization

1. Introduction

Data Structures and Algorithms deal with the systematic organization, storage, and processing of data in a computer. Before studying advanced data structures such as stacks, queues, linked lists, trees, and graphs, it is necessary to understand the basic terminology used to describe data and its organization.

Elementary Data Organization refers to the basic ways in which individual data items and collections of data items are represented and stored in computer memory.

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2. Data

Data is a collection of raw facts, figures, symbols, or values that can be processed by a computer.

Examples:

• 25
• 85.5
• A
• Gopal
• 10101
• 15, 25, 35, 45

Data by itself may not convey complete meaning until it is processed or interpreted.

Example:
The values 78, 85, 92, 88 are data representing marks, but their meaning becomes clearer when associated with a particular student and subject.

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3. Information

Information is meaningful and processed data that can be used for understanding or decision-making.

For example:

Raw data: 78, 85, 92, 88

After processing:

"The student obtained an average mark of 85.75."

Thus:

Data → Processing → Information

Data is the input, while information is generally the meaningful output obtained after processing the data.

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4. Data Item

A data item is a single unit of data that represents a particular value or attribute.

Examples:

• Roll number = 101
• Name = "Rahul"
• Age = 20
• Marks = 85.5

A data item may be elementary (atomic) or composite.

Elementary Data Item

An elementary data item cannot normally be divided into smaller meaningful components for the intended application.

Example:

int age = 20;

Here, age is an elementary data item.

Composite Data Item

A composite data item consists of multiple related data items.

For example, a student's record may contain:

Roll Number

Name

Age

Marks

Together, these form a composite representation of a student.

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5. Data Type

A data type specifies the kind of value that a variable can store and the operations that can be performed on that value.

In C, commonly used data types include:

Data Type	Typical Example
char	'A'
int	25
float	3.14
double	25.6789

For example:

int age = 20;

float percentage = 82.5;

char grade = 'A';

The data type determines how the compiler interprets and stores the value.

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6. Variable

A variable is a named memory location used to store a value that may change during program execution.

Example:

int marks = 85;

Here:

• int → data type
• marks → variable name
• 85 → value

Conceptually, memory can be represented as:

The exact memory address and size depend on the system and compiler.

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7. Elementary Data Organization

Elementary data organization deals with the representation and storage of basic data items in memory.

The simplest forms include:

1. Single data item / variable
2. Array
3. Structure
4. Other composite representations built from these basic forms

The objective is to organize data so that it can be stored, accessed, processed, and modified efficiently.

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8. Array

An array is a collection of elements of the same data type stored in logically consecutive memory locations.

Example:

int marks[5] = {85, 90, 78, 92, 88};

The array contains five integer elements:

Index	Value
0	85
1	90
2	78
3	92
4	88

The elements are accessed using an index.

printf("%d", marks[2]);

Output:

78

For an array, direct access using an index is efficient because the address of an element can be calculated from its index.

For a one-dimensional array:

where:

• LOC(A[i]) = address of element A[i]
• Base(A) = address of the first element
• i = index
• w = size of each element in bytes

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9. Record

A record is a collection of related data items describing a particular entity.

For example, a student record may contain:

Roll Number

Name

Branch

Semester

Marks

In C, a record can be represented using a structure.

struct Student

{

    int rollNo;

    char name[30];

    float marks;

};

A structure allows different types of data to be grouped under one name.

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10. Field

A field is an individual attribute or component of a record.

For:

struct Student

{

    int rollNo;

    char name[30];

    float marks;

};

the fields are:

• rollNo
• name
• marks

Each field represents a particular characteristic of the student.

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11. File

A file is a collection of related records stored on secondary storage such as an SSD or hard disk.

For example, a student file may contain:

Roll No.	Name	Marks
101	Amit	85
102	Ravi	78
103	Neha	91

Here, each row can be considered a record, while the columns represent fields.

Thus, a simplified organization is:

Data Item → Field → Record → File

This hierarchy is useful for understanding how larger collections of data are organized.

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12. Key

A key is a data item or combination of data items used to identify or locate a record.

For example, in a student database:

Roll Number = 101

may be used as the key for identifying a particular student record.

A good key should allow records to be identified efficiently and, when required, uniquely.

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13. Data Structure

A data structure is a systematic way of organizing and storing data so that operations such as accessing, inserting, deleting, searching, and sorting can be performed efficiently.

Examples include:

• Array
• Linked List
• Stack
• Queue
• Tree
• Graph
• Hash Table

Data structures can broadly be classified as:

Primitive Data Structures

• Integer
• Character
• Float
• Pointer, etc.

Non-Primitive Data Structures

• Array
• Linked List
• Stack
• Queue
• Tree
• Graph, etc.

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14. Abstract Data Type (ADT)

An Abstract Data Type (ADT) describes a data structure in terms of:

• the data it represents, and
• the operations that can be performed on that data,

without specifying the internal implementation.

For example, a Stack ADT supports operations such as:

• push()
• pop()
• peek()

A stack may be implemented using either an array or a linked list. The ADT focuses on what operations are available, rather than exactly how they are implemented.

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15. Data Organization and Memory

Data organization is closely related to memory organization.

A computer stores data in memory locations identified by addresses. The organization selected determines how easily and efficiently data can be accessed.

For example:

• A variable stores a single value.
• An array stores multiple homogeneous values.
• A structure groups related heterogeneous values.
• A linked list connects dynamically allocated nodes.
• A tree represents hierarchical relationships.
• A graph represents relationships between entities.

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16. Important Terminology at a Glance

Term	Meaning
Data	Raw facts and values
Information	Processed and meaningful data
Data Item	A single unit of data
Data Type	Specifies the type of value stored
Variable	Named memory location
Field	Individual component of a record
Record	Collection of related fields
File	Collection of related records
Key	Data used to identify a record
Array	Collection of similar elements
Data Structure	Organized representation of data
ADT	Logical description of data and its operations

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17. Example: Student Data Organization

Consider the following student:

Roll No. : 101

Name     : Ankit

Branch   : CSE

Marks    : 86.5

This can be viewed hierarchically as:

Student → Record → Fields → Individual Data Items

In C:

struct Student

{

    int rollNo;

    char name[30];

    char branch[10];

    float marks;

};

The structure provides an elementary mechanism for organizing related information about one entity.

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18. Important Points for Examination

1. Data represents raw facts and values.
2. Information is processed and meaningful data.
3. A data item represents a single unit of data.
4. A variable represents a named memory location.
5. An array stores elements of the same data type.
6. A record contains related fields describing an entity.
7. A field is an individual component of a record.
8. A file is a collection of related records.
9. A key helps identify or locate a record.
10. A data structure organizes data for efficient processing.
11. An ADT specifies data and operations independently of implementation.

Summary

Elementary data organization forms the foundation for the study of Data Structures and Algorithms. Data is represented using basic data types and variables and can be organized into arrays, records, files, and more sophisticated data structures. Understanding concepts such as data item, field, record, key, array, variable, and data structure is essential before studying advanced structures such as linked lists, stacks, queues, trees, and graphs.