Lecture Notes on Instances and Schemas

Introduction

• Focus on two important terminologies in database management systems: Instances and Schemas.

Analogy of Software Programming

• Software Development: Involves programming languages.
• Variables: Defined by programmers (e.g., variable a).
• Variable Value:
  • Holds a value that can change (e.g., a = 20).
  • The variable type determines the structure and size (e.g., integer type in C = 2 bytes).

Understanding Schemas

• Definition of Schema: Overall design of a database.
• Database: A collection of tables.
• Table: Data organized in rows and columns.
• Example: Banking database consists of multiple tables like customer, accounts, loans, etc.
• Relation to Analogy:
  • Database schema = variable declaration (the structure is fixed).
  • Changes to data in tables do not often affect schema.

Characteristics of Schema

• Once a schema is fixed, it is not frequently changed.
• Changes are possible but require database administrator intervention.
• Type Definition Example:
  • Student Record Structure:
    • Role number (numeric, max size 5)
    • Name (char, max size 25)
    • Class (char, max size 10)

Real-time Example: University Database

• Department Table: Fields include department name, building, budget, head of department.
• Course Table: Fields include course ID, title, department name, credits.
• Student Table: Fields include role number, name, department name, total credits.

Data Abstraction

• Hides the complexity of physical storage from programmers.
• Database administrators have additional responsibilities and knowledge of physical organization.

Understanding Instances

• Definition of Instance: Collection of interrelated data at a particular moment.
• Database Change: Data can be added or deleted, leading to changes in instances.
• Example: University database with changing student records (e.g., new admissions).
• Relation to Analogy:
  • Database instance = value of a variable that keeps changing.

Levels of Abstraction in Databases

1. View Level: Sub-schemas exist at this level.
2. Logical Level: Logical schema of the database.
3. Physical Level: Actual physical storage of data.

Conclusion

• Understanding schemas and instances is crucial for database management.
• Thank you for participating in the presentation.