Database Concepts Chapter Notes | Informatics Practices for Class 11 - Humanities/Arts PDF Download

Introduction

• Data management is crucial for organizations, such as schools, to store and handle information electronically.
• Example: A school maintains student data, including attendance records and guardian details.
• Class teachers manually mark daily attendance in a register, recording 'P' for present or 'A' for absent against each student's roll number.
• For a class of 50 students and 26 working days in a month, teachers record 50 × 26 = 1300 entries manually, which becomes tedious as data volume increases.
• Limitations of manual record keeping include:
  • Repetitive entry of student details (e.g., roll number, name) when students are promoted to the next class.
  • Inconsistencies in writing student details each month, such as incorrect names or skipped records.
  • Data loss if the attendance register is lost or damaged.
  • Errors in manual consolidation of attendance records.
• Office staff manually maintain student details (roll number, name, date of birth) and guardian details (guardian name, contact number, address) for correspondence.
• Manual systems make it difficult to find, delete, or modify information from large volumes of paper records.
• Computerized systems allow:
  • Copying student details to new attendance files when students are promoted.
  • Easy retrieval of student or guardian data.
  • Adding details for new students.
  • Modifying existing student or guardian details.
  • Deleting data when a student leaves the school.

File System

• A file is a container for storing data on a computer, saved on storage devices.
• File contents can include text, program code, comma-separated values (CSV), pictures, audio/videos, or web pages.
• Files can be accessed directly and searched for specific data.
• To access file data via software (e.g., displaying a monthly attendance report on a school website), custom programs must be written.
• Example: A school stores student and attendance data in two files:
• STUDENT file(Table 7.1) contains:
  • RollNumber: Student’s roll number.
  • SName: Student’s name.
  • SDateofBirth: Student’s date of birth.
  • GName: Guardian’s name.
  • GPhone: Guardian’s phone number.
  • GAddress: Guardian’s address.
• ATTENDANCE file(Table 7.2) contains:
  • AttendanceDate: Date of attendance.
  • RollNumber: Student’s roll number.
  • SName: Student’s name.
  • AttendanceStatus: 'P' (present) or 'A' (absent).

Limitations of a File System

• File systems become difficult to manage as the number of files and data volume grows.

Specific limitations include

Difficulty in Access:

• Files lack built-in data retrieval mechanisms; application programs are required.
• Developers may not anticipate all access needs, making it hard to retrieve data in desired formats.
• Additional programs must be written for specific data access requirements.

Data Redundancy:

• Redundancy occurs when the same data is duplicated across files.
• Example: Student names appear in both STUDENT and ATTENDANCE files.
• Example: Guardian details (e.g., Himanshu Shah) are repeated for multiple students in the STUDENT file.
• Redundancy wastes storage and may lead to data inconsistency.

Data Inconsistency:

• Inconsistency arises when duplicated data across files do not match.
• Example: If a student’s name is updated in one file but not another, the data becomes inconsistent.
• Example: If a student leaves, their details must be deleted from both files; failure to update one file causes inconsistency.
• Inconsistency is likely when different people maintain separate files.

Data Isolation:

• STUDENT and ATTENDANCE files are related but lack a direct link or mapping.
• Separate programs are needed to access each file.
• In complex systems, files created by different people at different times may have varying formats, complicating data retrieval.
• Developers must understand each file’s structure to write retrieval programs.

Data Dependence:

• Data is stored in a specific format; changing the format requires updating all related application programs.
• Without updates, programs may fail to access the file correctly.
• This dependency complicates file structure modifications.

Controlled Data Sharing:

• Different users (e.g., teachers, office staff, guardians) require different access levels.
• Example: Guardians and staff should only view attendance data, while teachers can update it.
• File systems struggle to enforce such access controls through application programs.

Database Management System

• A Database Management System (DBMS) is software for creating and managing databases, overcoming file system limitations.
• DBMS allows users to create, store, manage, update, and retrieve data efficiently.
• Examples of DBMS include MySQL, Oracle, PostgreSQL, SQL Server, Microsoft Access, and MongoDB.
• DBMS hides storage and maintenance details, providing an abstract view of data.
• It includes programs for accessing, modifying, and retrieving data.
• DBMS acts as an interface between the database and users or applications.
• Data retrieval is done through querying, using special commands.
• Users can modify the database structure via the DBMS.
• Applications of databases include:
  • Banking: Customer info, accounts, loans, transactions.
  • Crop Loan: Farmer data, land details, loan history.
  • Inventory Management: Products, customers, orders, deliveries.
  • Organization Resource Management: Employee records, salaries, departments.
  • Online Shopping: Item descriptions, user logins, preferences.

File System to DBMS

Converting the school’s STUDENT and ATTENDANCE files into a database requires:

• Removing SName from the ATTENDANCE file, as it’s redundant with the STUDENT file; RollNumber links the files.
• Splitting the STUDENT file into STUDENT and GUARDIAN files to avoid redundant guardian data (e.g., for siblings).
• Adding a unique GUID (Guardian ID) column to the GUARDIAN file to distinguish guardians, as names may be duplicated.
• Using GUID in the STUDENT file to link to the GUARDIAN file, since phone numbers may change.

The resulting database, STUDENTATTENDANCE, includes three tables:

• STUDENT: RollNumber, SName, SDateofBirth, GUID.
• GUARDIAN: GUID, GName, GPhone, GAddress.
• ATTENDANCE: AttendanceDate, RollNumber, AttendanceStatus.

DBMS maintains a centralized data repository, accessible by multiple users (e.g., office staff, teachers) simultaneously.

Key Concepts in DBMS

Database Schema:

• The design of a database, representing table names, columns, data types, constraints, and relationships.
• Also called the visual or logical architecture, showing data organization.

Data Constraint:

• Restrictions on data in table columns, defined during table creation.
• Example: Mobile number column restricted to 10-digit non-negative integers.
• Example: RollNumber column set to NOT NULL and UNIQUE to ensure unique student IDs.
• Constraints ensure data accuracy and reliability.

Meta-data or Data Dictionary:

• Database schema and constraints stored in a database catalog, called meta-data (data about data).

Database Instance:

• The state of a database at a given time, initially empty when the schema is defined.
• Data loading creates an instance; queries and manipulations (insert, update, delete) change the instance.

Query:

• A request to retrieve information from one or more tables.
• Example: “Find names of students present on 2000-01-02.”
• Written in a query language (e.g., SQL, discussed in Chapter 8).

Data Manipulation:

• Includes Insertion, Deletion, and Update operations.
• Example: Adding a new student’s details to STUDENT and GUARDIAN tables (Insertion).
• Example: Removing a student’s data from all tables when they leave (Deletion).
• Example: Updating a guardian’s phone number in the GUARDIAN table (Update).

Database Engine:

• The underlying component of a DBMS that creates databases and handles queries for data retrieval and manipulation.

Relational Data Model

A data model defines the database structure, data representation, relationships, and constraints.

• The Relational Data Model is the most common, used in Relational DBMS (RDBMS).
• Other models include object-oriented, entity-relationship, document, and hierarchical models.

In the relational model:

• Tables are called relations, storing data in columns.
• Each table has unique column names.
• Each row (tuple) represents a related set of values for an entity.
• Example: Each row in the GUARDIAN table represents a guardian’s details (GUID, name, phone, address).

Relations are interconnected, not independent:

• ATTENDANCE’s RollNumber links to STUDENT records.
• STUDENT’s GUID links to GUARDIAN records.
• Linking attributes ensure database integrity and valid data retrieval.

Key terminologies:

• Relation: A table (e.g., GUARDIAN).
• Tuple: A row in a table, representing a record.
• Attribute: A column in a table, representing a feature.
• Domain: The set of permissible values for an attribute (e.g., 10-digit numbers for GPhone).
• Degree: Number of attributes in a relation (e.g., GUARDIAN has degree 4).
• Cardinality: Number of tuples in a relation (e.g., GUARDIAN has cardinality 5).

Three Important Properties of a Relation

Property 1 (Attributes):

• Each attribute in a relation has a unique name.
• The sequence of attributes is immaterial.

Property 2 (Tuples):

• Each tuple is distinct; no two tuples can have identical values for all attributes.
• Tuples are uniquely identified by their contents.
• The sequence of tuples is immaterial, despite appearing ordered in tables.

Property 3 (State of Relation):

• All values in an attribute must be from the same domain (same data type).
• Values must be atomic (indivisible into meaningful subparts), e.g., GPhone is a single 10-digit number.
• No attribute can have multiple values in one tuple, e.g., GPhone cannot list multiple numbers.
• NULL represents unknown or non-applicable values, e.g., GPhone is NULL if not provided.

Keys in a Relational Database

Tuples must be distinct; at least one attribute must have unique, non-NULL values to identify each tuple.

• Keys impose constraints on attribute values and inter-relation references, defined during database design.

Candidate Key

• Attributes that take distinct values and can uniquely identify tuples.
• Multiple attributes may qualify as candidate keys.
• Example: In the GUARDIAN table, GUID and GPhone are unique, making them candidate keys.

Primary Key

• The candidate key chosen by the designer to uniquely identify tuples.
• Remaining candidate keys are alternate keys.
• Example: If GUID is chosen as the primary key for GUARDIAN, GPhone becomes an alternate key.

Composite Primary Key

• If no single attribute uniquely identifies tuples, multiple attributes are combined as the primary key.
• Example: In the ATTENDANCE table, neither RollNumber nor AttendanceDate alone is unique, but their combination is unique (as a student is marked once per day).
• Thus, {RollNumber, AttendanceDate} forms the composite primary key.

Foreign Key

• An attribute in one relation whose values are derived from the primary key of another relation.
• Links two relations, with the referencing relation called the foreign relation and the referenced relation called the primary or master relation.
• Foreign keys can take NULL values if not part of the foreign table’s primary key.
• Example: In the STUDENTATTENDANCE database:
  • RollNumber in ATTENDANCE references RollNumber in STUDENT.
  • GUID in STUDENT references GUID in GUARDIAN.
• Foreign keys are shown in schema diagrams as arrows from the foreign key to the primary key of the referenced table.