Database Management System Overview

Organize data into tables (relations) consisting of rows and columns.
Each table has a unique key to identify records.
Supports relationships between tables using foreign keys.
Enforces data integrity through constraints (e.g., primary key, unique, foreign key).
Examples: MySQL, PostgreSQL, Oracle Database.

SQL (Structured Query Language) is used to communicate with relational databases.
Common SQL commands:
- SELECT: Retrieve data from one or more tables.
- INSERT: Add new records to a table.
- UPDATE: Modify existing records.
- DELETE: Remove records from a table.
Clauses:
- WHERE: Filter records.
- ORDER BY: Sort results.
- GROUP BY: Aggregate records (e.g., COUNT, SUM).
- JOIN: Combine rows from two or more tables based on a related column.

Ensures data integrity and consistency in database operations.
Transactions have four properties (ACID):
- Atomicity: All operations in a transaction are completed; if one fails, the whole transaction fails.
- Consistency: Transactions bring the database from one valid state to another.
- Isolation: Transactions are executed independently; concurrent transactions do not affect each other.
- Durability: Once a transaction is committed, it remains so even in case of a system failure.
Example commands: COMMIT, ROLLBACK.

Process of organizing data to reduce redundancy and improve data integrity.
Involves dividing large tables into smaller, related tables.
Normal forms (1NF, 2NF, 3NF, BCNF, etc.):
- 1NF: Eliminate duplicate columns; ensure each cell contains atomic values.
- 2NF: Eliminate partial dependencies (non-key attributes depend on a part of a composite key).
- 3NF: Eliminate transitive dependencies (non-key attributes depend on other non-key attributes).

Centralized repository for storing large volumes of data from multiple sources.
Optimized for query and analysis rather than transaction processing.
Facilitates business intelligence and reporting tasks.
Key components:
- ETL (Extract, Transform, Load): Process of collecting data from various sources, transforming it for analysis, and loading it into the warehouse.
- OLAP (Online Analytical Processing): Tools that enable complex queries and data analysis.
Supports historical data analysis and trend forecasting.

Organize data into tables (relations) containing rows and columns.
Each table has a unique key, ensuring record identification.
Relationships between tables are established using foreign keys.
Data integrity is enforced through constraints such as primary key and unique constraints.
Notable relational database management systems include MySQL, PostgreSQL, and Oracle Database.

SQL (Structured Query Language) serves as the medium for interaction with relational databases.
Common commands in SQL:
- SELECT: Used to retrieve data from tables.
- INSERT: Adds new records to a specified table.
- UPDATE: Modifies existing records in a table.
- DELETE: Removes specified records from a table.
Key clauses enhance query functionalities:
- WHERE: Filters records based on conditions.
- ORDER BY: Sorts results in a specified order.
- GROUP BY: Aggregates records based on specified attributes (e.g., COUNT, SUM).
- JOIN: Combines rows from multiple tables based on a related column.

Maintains data integrity and consistency during database operations.
Transactions follow four core properties known as ACID:
- Atomicity: Ensures all operations within a transaction succeed or fail together.
- Consistency: Verifies that transactions transition the database from one valid state to another.
- Isolation: Guarantees that concurrent transactions do not interfere with one another.
- Durability: Assures that once a transaction is committed, it remains intact despite system failures.
Common transaction commands include COMMIT (finalize changes) and ROLLBACK (revert changes).

A methodical approach to organizing data aimed at minimizing redundancy and maximizing data integrity.
Involves breaking down large tables into manageable, related tables.
Normal forms are used to guide the normalization process:
- 1NF: Ensures data is atomic with no duplicate columns.
- 2NF: Removes partial dependencies by ensuring non-key attributes depend on the entire composite key.
- 3NF: Eliminates transitive dependencies, confirming that non-key attributes are not dependent on other non-key attributes.

A centralized platform designed for storing large quantities of data collected from various sources.
Optimized primarily for query and analysis rather than for transaction processing.
Enhances business intelligence and aids in reporting initiatives.
Key components include:
- ETL (Extract, Transform, Load): The process for gathering data, transforming it for analysis, and storing it in the warehouse.
- OLAP (Online Analytical Processing): Tools facilitating complex data analysis and queries.
Supports the analysis of historical data and assists in trend forecasting.