Data abstraction is a concept in database management that involves hiding unnecessary details from users, allowing them to interact with the system in a simplified manner.
There are three levels of data abstraction:
- Physical Level:
- What: Describes how the data is actually stored in the database.
- Details: Involves complex low-level data structures.
- Example: Knowing the details of file storage, disk structures, or data storage formats.
- Logical Level:
- What: Describes what data is stored in the database and the relationships between the data.
- Details: Focuses on a small number of relatively simple structures.
- Example: Understanding the entities, attributes, and relationships in a relational database without delving into specific storage details.
- View Level:
- What: The highest level of abstraction, presenting a simplified, user-specific view of the database.
- Details: Provides a subset of the entire database relevant to a specific user or application.
- Example: A user interface showing only certain fields or records based on a user’s role or specific needs.
Explanation in Simpler Terms:
- Physical Level: Imagine you have a library. At the physical level, it’s like knowing exactly where each book is stored on each shelf in the library.
- Logical Level: Now, think of the logical level as understanding what types of books are in the library (e.g., fiction, non-fiction) and how they are categorized, without worrying about the specific shelf location of each book.
- View Level: Finally, the view level is like someone walking into the library and seeing a curated display of books on a special shelf – tailored to their interests. They only see what’s relevant to them, and they don’t need to know all the intricate details of the library’s organization.