Lecture 1: Database Systems

Data, Information, and Knowledge

Data

• Raw facts not yet processed to reveal meaning.
• Serve as the building blocks of information.
• Require proper management for generation, storage, and retrieval.

Information

• Produced by processing data.
• Reveals meaning and enables knowledge creation.
• Must be accurate, relevant, and timely for effective decision-making.

Key Points

• Data -> processed -> Information -> supports decision making.
• Sound decisions are essential for organizational survival in competitive environments.
• Raw data must be formatted correctly for storage, processing, and presentation.
  • Example:
    • Julian date format: 2025001 -> January 1, 2025
    • Yes/No responses stored as Y/N, true/false, or 0/1.
  • Complex data types (images, audio, video) require additional formatting.

Database Concepts

Definition

A database is a shared, integrated computer structure that stores:

• End-user data: raw facts of interest to users.
• Metadata: data about data (describes characteristics and relationships).

Importance

• Integrates data for easy access and management.
• Metadata defines structure and relationships, enabling efficient organization.

Types of Databases

By User

• Single-user: supports one user at a time.

  • Example: desktop databases on personal PCs.

• Multi-user: supports concurrent users.

  • Workgroup DB – limited to a department.
  • Enterprise DB – organization-wide.

By Network Distribution

• Centralized: data stored at a single site.
• Distributed: data spread across multiple sites.
• Cloud: hosted on cloud services with defined performance metrics.

By Purpose

• General-purpose: Contains a wide variety of data for many uses.
• Discipline-specific: focused on particular subject areas.

By Operation

• Operational (OLTP): supports daily operations.
• Analytical (OLAP): supports tactical/strategic decisions via historical data.
• Data Warehouse: optimized for decision support (ETL processes).

By Business Type

• OLAP systems: retrieve, process, and model warehouse data.
• Business Intelligence (BI): analyze data to support decision-making.

By Data Type

• Unstructured: raw, unprocessed form (e.g., images, videos).
• Structured: formatted for storage and retrieval.
• Semistructured: partially processed (e.g., XML).

Database Design

Focus

Designing the structure that stores and manages end-user data.

Characteristics

• Well-designed database:

  • Simplifies data management.
  • Produces accurate and valuable information.

• Poorly designed database:

  • Causes inconsistencies and hard-to-trace errors.

Summary

Concept	Description
Data	Raw facts that form the base of information
Information	Processed data that provides meaning
Metadata	Data describing other data
Database	Structured collection of data + metadata
Database Design	Process of creating efficient data structures
Database Types	Classified by user, network, purpose, operations, business, and data type