Oracle Academy: Database Foundations

Oracle Academy: Database Foundations

Introduction to Databases

Lesson Objectives

  • Differentiate between data and information.

  • Define database.

  • Describe the elements of a Database Management System (DBMS).

  • Identify transformations in computing.

  • Identify business and industry examples where database applications are used.

Data Versus Information

Definitions

  • Data:

    • Raw material from which conclusions can be drawn; facts from which new facts can be deduced.

    • Collected facts about a topic or item.

  • Information:

    • Knowledge, intelligence; a specific piece of data with a particular meaning or function.

    • Often the result of combining, comparing, and performing calculations on data.

Explanation

  • The difference between data and information is highlighted through examples such as test scores:

    • Each student's test score is considered data.

    • The calculated class average or school average from these scores represents information.

Example of Data and Information

  • Data in:

    • 2015: $1,000,000

    • 2016: $2,000,000

  • Information out:

    • Next year's budget suggestions based on accumulated data.

  • Other forms of data include:

    • “Article VI prohibits use of school property for…”

    • 312 graduates with a 98% math exam pass rate leading to student performance information.

Database Definition

  • Database:

    • A centralized and structured set of data stored on a computer system.

    • Provides facilities for:

    • Retrieving data.

    • Adding new data.

    • Modifying existing data.

    • Deleting data when required.

    • Transforming retrieved data into useful information.

Database Application

  • A database application is a software program that interacts with a database to access and manipulate data.

  • A database is typically managed by a Database Administrator (DBA).

Introduction to Relational Databases

  • A relational database:

    • Stores information in tables organized by rows and columns.

  • Table:

    • A collection of records.

  • Row:

    • Also known as a record or instance.

  • Column:

    • Also referred to as a field or attribute.

  • Each table in a relational database can have relationships with other tables through shared fields (columns).

Example of Relational Database

  • Consider tables such as Order Details and Customer:

    • These tables relate to each other through common attributes like ID and Customer ID.

    • Information about an order includes details linked to a customer, allowing for insights on purchasing behaviors and marketing strategies.

Elements of a Database Management System (DBMS)

  • A DBMS is software that manages:

    • Storage

    • Organization of data

    • Retrieval of data

  • Key elements of a DBMS include:

    • Kernel Code: Manages memory and storage.

    • Data Dictionary: Holds metadata about the database.

    • Query Language: Enables applications to access data.

Key Computing Terms

  • Hardware: Physical components of a computer (keyboard, monitor, mouse, disk drive, memory).

  • Software: Programs that instruct hardware on what to do.

  • Operating System: Software that directly manages hardware (e.g., Windows).

  • Application: Software performing specific tasks for users (e.g., Microsoft Word).

  • Client: A workstation or desktop with user interface elements.

  • Server: A powerful computer processing requests from clients and providing data.

Client-Server Relationship

  • Client and server communications involve:

    • Clients querying servers for information.

    • Servers processing requests, retrieving required data, and returning it to clients.

Transformation in Computing

Historical Progression

  1. 1970s: Mainframe Computing

    • Database systems integrated hardware and software using dumb terminals.

    • Terminals processed commands using mainframes as storage.

  2. 1980s: Desktop Computing

    • Increased processing migrated from mainframes to client PCs (smart clients).

    • GUI applications emerged, leading to popular software such as Office applications.

  3. 1990s: Client/Server Computing

    • Combination of centralized and local processing with the use of the Internet for requests.

    • Data managed on database servers, with web applications accessing essential business functionalities.

  4. 2000s: Grid Computing

    • Utilizes pooled computing resources across networked servers like utility services.

    • Operates as an efficient information processing network.

  5. 2010s: Cloud Computing

    • Internet-based processing services providing resources like IaaS, PaaS, and SaaS.

    • Examples range from renting servers to directly accessing software over the web.

History of the Database Timeline

  • 1960s: Price drop of computers and increased storage capabilities for businesses.

  • 1970-72: E.F. Codd's relational model proposal.

  • 1976: P. Chen introduces the entity relationship model for database design.

  • Early 1980s: Launch of early relational database systems such as Oracle's Version 2.

  • Mid-1980s: SQL popularity.

  • 1990s: Boom in database tools due to the Internet.

  • 2000s: Significant growth of database applications in various sectors.

  • 2010s: Rise of Cloud Computing, transforming into a multi-billion dollar industry.

Examples of Database Applications

  • Education: Managing details about courses, students, and faculty.

  • Finance: Storing customer and transaction information.

  • Transport: Airline and railway reservations.

  • Healthcare: Maintaining patient records.

  • Telecommunications: Storing network and billing information.

  • Digital Publishing: Managing online data and resources.

Summary

  • In this lesson, students learned to:

    • Differentiate between data and information.

    • Define a database and its management system.

    • Recognize computing transformations.

    • Identify various real-world applications of databases across industries.