Lec-6: Three Schema Architecture | Three Level of Abstraction | Database Management System

Three Levels of Abstraction in DBMS

Introduction to Three Schema Architecture

• The video introduces the concept of three levels of abstraction in Database Management Systems (DBMS), also known as the three schema architecture.

• The speaker requests viewers to subscribe and share the channel, emphasizing its educational purpose.

Understanding Schema

• A schema is defined as the structure for storing data, which can include various types such as student data or e-commerce data from platforms like Flipkart and Amazon.

• Data is organized into tables with columns (attributes) and rows (records), illustrating a relational database model.

Levels of Schema

• The three levels of schema are identified: external schema (view level), conceptual schema, and physical schema (internal level).

• Introduced in 1970, this architecture aims to achieve data independence, meaning users do not need to know how or where their data is stored.

Data Independence and Abstraction

• Data independence allows users to interact with data without needing knowledge about its storage details; this is referred to as data abstraction.

• An example provided is Gmail, where users access emails without knowing their physical storage locations.

External Schema Explained

• The external schema, also called view level, determines how data is presented to different users based on their roles.

• Practical applications today still utilize these theoretical models despite advancements since 1970.

User-Specific Views

• In a university management system example, students have specific views showing relevant information like marks and attendance while faculty have different permissions.

• Different user roles necessitate distinct views for security reasons; students cannot access faculty-specific functionalities like entering marks or checking salaries.

Conclusion on Views

Understanding Database Schemas and Their Components

Different Perspectives on Data Views

• The example illustrates that students, faculty, and deans each have their own perspectives on data. This highlights the subjective nature of data interpretation based on user roles.

• When logging into applications like Flipkart or Amazon, the initial view presented is referred to as an external schema, which shapes user interaction with the system.

Conceptual Schema Explained

• The conceptual schema represents how data is structured within a database. It defines what information is stored (e.g., student roll number, name, age).

• Before creating a database, it’s essential to establish a conceptual view or blueprint of the data structure using models like E-R diagrams.

Relational Model and Table Relationships

• The E-R model serves as a conceptual framework for organizing data into tables representing different entities (e.g., students, courses).

• In relational databases, various tables are created to store information about entities such as students and courses. Understanding relationships between these tables is crucial for effective database design.

Blueprint of Data Structure

• The conceptual schema acts as a blueprint detailing table structures and relationships before actual implementation begins.

• Physical schemas detail where data is stored physically (e.g., hard disks), while database administrators manage this storage process.

Roles in Database Management

• Three key roles exist in database management: interface designers work on front-end applications; database designers create blueprints; and database administrators oversee data storage decisions.

• Administrators determine whether data should be centralized (stored in one location) or distributed across multiple locations globally.

Storage Formats and User Interaction

• Data can be stored either centrally or distributed; centralized means all data resides in one place while distributed involves multiple global locations.

Understanding Data Storage and Abstraction

The Nature of Data Storage

• Data is stored in hard disks as files rather than in a tabular format, despite user interfaces presenting it in tables (e.g., train schedules).

• The physical schema defines what data is actually stored, emphasizing the role of the physical schema in managing real data storage.

Concept of Data Independence

• Users are not directly connected to the database; instead, there are layers that facilitate interaction with the data.

• Three layers are implemented to provide data abstraction, allowing users to access data without needing to understand its underlying structure or storage.

User Experience and Cloud Computing

• Users expect seamless access to their data (e.g., emails), regardless of the technology used behind the scenes, such as cloud computing.