Module-1

DBMS - Notes

Raw, unprocessed facts or details without context or meaning. Data is unorganized and often collected from observations, measurements, or recordings.

Examples: Numbers, dates, text, images, or symbols that need interpretation (e.g., "25," "2023-09-04," or "John").

Processed, organized, or structured data that is meaningful and useful for decision-making or understanding.

Examples: A report showing the average temperature, a summarized sales report, or an analyzed dataset showing trends.

Record: A collection of various types of data of similar field.

Data file: A collection of records, sometimes called a table.

Information stored in a way that it remains available after system restart. Saved on devices like hard drives, SSDs, or databases.

An organized collection of data that allows easy retrieval, insertion, updating, and deletion.

A file is a collection of data stored on a computer or device. Files can contain text, images, videos, or programs.

Software to organize, store, retrieve, and manage files using folders, search, backup, etc.

The way data is arranged within a file, e.g., headers, metadata, data content.

How files are arranged on a storage device. Can be hierarchical or flat.

Sequential: Simple, efficient for sequential access. Poor for random access.
Indexed Sequential: Uses index for fast random access. Requires extra storage.
Direct: Uses hashing. Efficient but prone to collisions.
Clustered: Based on common attribute. Fast for specific queries.
Hash: Advanced hashing to reduce collisions.
Multi-level Indexing: Handles large datasets efficiently.

A DBMS helps organize, store, and retrieve data efficiently using tables. It supports data manipulation, retrieval, security, and sharing.

Manual: Paper records and ledgers.

Relational: Tables and SQL introduced by Edgar F. Codd.

NoSQL: For large, flexible, scalable systems (MongoDB, Redis, etc.).

Cloud: Cloud-hosted databases with low maintenance and high accessibility.