Week-2-Intro-to-Databases-and-Data-Modeling

Introduction to Database Systems

  • Database systems handle data storage, management, and access.

Data vs Information

  • Data: Groups of information representing qualitative or quantitative attributes.

  • Information: Refined or processed data transformed into meaningful forms for users.

Database

  • A database is an organized collection of data that allows easy access, management, and updating.

Database Management System (DBMS)

  • A collection of interrelated data along with programs to access and manipulate that data.

  • General-purpose software that facilitates defining, constructing, and sharing databases.

Components of Database Systems

  • Database System Components:

    • Database

    • DBMS

    • Application Programs

Database Environment

  • A collective system of components for data management, which includes:

    • Software

    • Hardware

    • People

    • Techniques

Database Environment Components

  • Tools and roles in a database environment include:

    • CASE (Computer Aided Software Engineering Tools)

    • Repository

    • DBMS

    • Application Programs

    • User Interface

Examples of DBMS

  • Some common DBMS include:

    • Sybase

    • Microsoft SQL Server

    • DB2

    • Oracle

    • PostgreSQL

    • MySQL

Evolution of Databases

  • 1960: Introduction of file processing systems.

  • 1970: Development of hierarchical and network database models.

  • 1980: Introduction of relational databases by Dr. E.F. Codd.

  • 1990: Development of object-oriented databases.

  • 2000 and beyond: Multi-tier client-server architecture.

Ranges of Databases

  • Personal Database: For individual use on PCs or mobile devices.

  • Workgroup Database: Supports collaboration for small teams.

  • Department Database: Supports larger groups with diverse functions.

  • Enterprise Database: Encompasses organizational-wide data needs.

Types of Databases

  • Hierarchical Database: Visualized as an upside-down tree; a single table is the root.

  • Network Database: Uses sets to reduce data redundancy.

  • Relational Database: Stores data in two-dimensional tables.

  • Object-Relational Database: Combines features of object-oriented models within relational databases.

Data Modeling

  • Process of creating a diagram that represents data structures and flows within a system.

  • Provides a blueprint for database design.

  • Facilitates effective data use to meet business requirements.

Importance of Data Modeling

  • Eliminates redundancy and reduces storage needs.

  • Enables efficient data retrieval.

Phases of Data Modeling

  1. Conceptual Model: Identifies various data sets and their flows; abstract and easy to enhance.

  2. Logical Model: Describes data flow and relationships with greater detail.

  3. Physical Model: Details how the logical model is implemented in a specific database system.

Components of Logical Model

  • Entities: Represent relevant sets of things or concepts.

  • Relationships: Associations between entities.

  • Attributes: Descriptive characteristics of entities.

Data Modeling Techniques

  • Hierarchical, Network, Relational, Entity-Relationship, Dimensional, Object-Oriented, and Graph Modeling: Various methods for structuring data based on relationships and characteristics.