Key Concepts in Information Management and Databases

Information Management (IM)

The process of collecting, storing, managing, and maintaining information in an organized way to ensure accessibility, security, and usefulness.

Information Lifecycle

The stages information goes through: Create, Use, Store, Destroy or Preserve, and Protect.

Physical Data

Information assets in physical form, such as papers, documents, and books.

Digital Data

Information assets in digital form, such as files, databases, and online information.

Importance of IM

Ensures organization, protection, efficient decision-making, cost reduction, and legal compliance.

Key Components of IM

Governance, Systems, Processes, Sharing & Delivery.

Five Pillars of IM

Leadership, Operations, Processes, Data, Technology.

Benefits of IM

Easy retrieval, cost savings, improved transparency, business continuity, and legal compliance.

RA 10173

The Data Privacy Act of 2012 in the Philippines, protecting personal data and privacy.

National Privacy Commission (NPC)

The Philippine agency overseeing data privacy and enforcing the Data Privacy Act.

Database

A collection of related data designed for a specific purpose.

Database Management System (DBMS)

A computerized system for creating, maintaining, and manipulating databases.

Characteristics of Database Approach

Self-describing nature, data abstraction, multiple views, and multi-user processing.

Database Administrator (DBA)

Manages security, performance, and user access in a database system.

Database Designer

Structures data for efficient storage and retrieval.

System Analyst

Determines requirements and develops specifications for database systems.

End User

Queries, updates, and reports data in a database system.

Advantages of DBMS

Reduces redundancy, restricts unauthorized access, supports complex relationships, ensures data integrity.

Relational Model

A data model introducing data abstraction and flexibility.

NoSQL Systems

Databases handling large-scale, unstructured data.

Data Abstraction

Suppressing details of data organization to highlight essential features.

Data Models

Concepts describing the structure of a database, including entities, attributes, and relationships.

High-Level Data Models

Provide concepts close to how users perceive data, such as entities and relationships.

Low-Level Data Models

Describe how data is stored on computer storage media.

Entities

Represent real-world objects or concepts in a database.

Attributes

Properties of interest describing entities.

Relationships

Associations between two or more entities.

Database Schema

A description of a database's structure, including tables, relationships, and constraints.

Schema Diagram

A visual representation of a database schema.

Database State

The data in a database at a particular moment in time.

Three-Schema Architecture

Internal, Conceptual, and External levels separating user applications from the physical database.

Data Definition Language (DDL)

Used to define database schemas.

Data Manipulation Language (DML)

Used for retrieving and updating data in a database.

DBMS Interfaces

Include menu-based, forms-based, graphical, and natural language interfaces.

Centralized DBMS

All DBMS functionality is carried out on one machine.

Client/Server Architecture

Separates client and server functions in a database system.

Relational Algebra

A procedural query language defining operations on relations.

Relational Calculus

A non-procedural query language using logical predicates.

Selection Operation

Retrieves specific rows from a table based on a condition.

Projection Operation

Retrieves specific columns from a table.

Join Operation

Combines tuples from two relations based on a condition.

Natural Join

Matches tuples based on common attribute names.

Cartesian Product

Combines every tuple from one table with every tuple from another.

Set Operations

Include Union, Intersection, and Set Difference.

Query Optimization

Improves database performance by reducing computational load.

Entity-Relationship (ER) Model

A high-level conceptual data model for designing databases.

ER Diagram

A visual representation of entities, attributes, and relationships in a database.

Cardinality Ratio

Specifies the maximum number of relationship instances an entity can participate in.

Participation Constraints

Specify whether an entity's existence depends on its relationship with another entity.

Specialization

Subdividing entities into subtypes.

Generalization

Merging subtypes into a higher-level entity.