Bases de Datos: Definición y Tipos

Definition and Purpose

• A database is a structured collection of data, organized and stored electronically.
• It enables efficient storage, retrieval, and management of information.
• Databases manage large amounts of data, acting as a centralized repository for access and manipulation.
• Purpose is to provide easy storage and retrieval, along with efficient data management.

Types of Databases

• Relational Databases: Data structured in tables with defined relationships. Queryable using SQL, examples include MySQL, PostgreSQL, and Oracle.
• NoSQL Databases: Non-relational, without a schema. Suitable for unstructured or evolving data, including MongoDB.
• Object-Oriented Databases: Organize data as objects, similar to object-oriented programming. Used for complex data with rich properties and relationships.
• Graph Databases: Represent data as nodes and edges, showing relationships. Useful for network analysis and recommendations.

Database Management Systems (DBMS)

• Software systems interacting with databases, enabling users to define, create, and maintain them.
• Tasks include data storage, query processing, security, and backup/recovery.
• Examples include MySQL, PostgreSQL, Oracle, and SQL Server.

Key Concepts

• Entity: Person, place, thing, or event, represented as a table.
• Attribute: Characteristic of an entity, a column in the table.
• Record: Data about a single instance of an entity, a row in the table.
• Field: Single piece of data within a record, a cell in the table.
• Primary Key: Unique identifier for each record in a table.
• Foreign Key: Field linking tables, referencing the primary key of another table.
• Schema: Database structure, defining entities, attributes, and relationships.

Data Modeling

• Designing database structure to meet needs, describing data organization.
• Entity-Relationship Diagrams (ERDs): Visual representations of entities, attributes, and relationships.

Database Design

• Crucial for efficient and effective databases.
• Normalization reduces redundancy and ensures data integrity.
• Data security and access control are important aspects.
• Future growth and changes must be considered.

Data Integrity

• Ensuring data accuracy and consistency within a database.
• Constraints enforce rules, and data validation is necessary.
• Data integrity is crucial to prevent errors, like incorrect data entry or updates.

Database Queries (SQL)

• Structured Query Language (SQL) manages and manipulates relational databases.
• Functions include querying, inserting, updating, and deleting data.
• Common SQL commands: SELECT, INSERT, UPDATE, DELETE, WHERE, JOIN.

Database Administration

• Managing databases effectively, including performance, security, and availability.
• Handling backups and recovery is essential.

Database Security

• Protecting data from unauthorized access, use, disclosure, disruption, modification, or destruction.
• Access controls limit user privileges; encryption secures sensitive data, and regular backups are essential.

Database Performance Tuning

• Optimizing database queries and overall system performance.
• Indexing techniques accelerate retrieval.
• Understanding query execution plans is key.

Cloud Databases

• Cloud-hosted databases growing, offering scalability and accessibility.
• Managed by providers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).

Data Warehousing and Business Intelligence

• Specialized databases for large, aggregated data from various sources.
• Support business intelligence initiatives and analytical reporting.

Este cuestionario explora la definición y el propósito de las bases de datos, así como sus diferentes tipos, incluyendo bases de datos relacionales y NoSQL. Aumenta tu comprensión sobre cómo se gestionan y organizan los datos para un acceso eficiente.