Database Management System Unit 1

Study Notes

Data: Facts that can be recorded or stored (e.g., person’s name, age, gender, weight).
Information: Processed data presented in context, making it useful.
Database: A collection of inter-related data, such as a library or university database.

Definition: A set of programs that manages databases. It combines data storage and manipulation capabilities.
Examples: MS SQL Server, Oracle, MySQL, SQLite, MongoDB.

Metadata: Data about data, including table names, column names, and user access privileges.
Data Dictionary: Repository containing metadata, often part of the system catalog.
Data Warehouse: Repository designed for reporting and analysis, storing vast amounts of data.
Field: A specific character or group of characters representing data (e.g., customer ID, name).
Record: A collection of logically related fields (e.g., ID, name, address, city forming customer records).

Railway Reservation System: Manages ticket bookings, train schedules, and updates users on train status.
Library Management System: Efficiently tracks book information, including availability and issue dates.
Banking: Supports daily transactions and record-keeping without requiring physical bank visits.
Universities and Colleges: Maintains records for student registrations, results, courses, and grades.
Telecommunications: Stores call details and manages billing for services.
Credit Card Transactions: Facilitates transaction tracking and management for users.

Types:
- 1-tier: Single-tier architecture with direct interaction between the user and database.
- 2-tier: Client-server model where client requests are sent to a server.
- 3-tier: Three-layer architecture separating user interface, application logic, and database management.

External Level: User's view of the database.
Conceptual Level: Community view reflecting the logical structure of the entire database.
Internal Level: Physical storage of data on a storage medium.

Hierarchical Data Model: Organizes data in a tree-like structure using parent-child relationships.
Network Data Model: Allows more complex relationships with multiple parent-child connections.
Relational Data Model: Uses tables to represent data and relationships.
Entity-Relationship Data Model (E-R): Visual representation showing entities and their relationships.