Week 1 - Introduction to Database and DBMS

• Data
  • Data is a collection of points with no discernible meaning
  • pure and simple fact
• Information
  • Information is data that is in some sort of structure and in context
  • Has meaning
• Knowledge
  • Information the has been assimilated in the mind
  • knowledge is to use data to strategically forward ones objective
• Wisdom
  • the application of knowledge
  • capacity to choose objectives that consist of ones value

• Shared, integrated computer structure that houses:
  • End user data (raw facts)
  • Metadata (data about data)
• Data that is held in a computer usually associated with a software that is used to update and create data

• A database system consists of:
  • Data (the database)
  • Software
  • Hardware
  • Users

Databases allows users to store, update, retrieve, organise, and protect their data

• End users
  • Uses the database to achieve some goals
• Application Developers
  • Writes software that allows the end user to interface with the database system
• Database administrator (DBA)
  • Create or modify the schema
  • Define and mange database system
  • Responsible for the structure of the database
  • and how it is stored
• Database systems programmer
  • Writes the database software itself

• Databases for Businesses
• Databases for Education
• Databases for Non-profits
• Databases for Household and family management
• Everyday uses for databases

• Collection of programs that manages database structure and controls access to data
• Makes database management more efficient and effective

• Solve many of the problems encountered in data management
  • e.g.
  • Data sharing
  • Increases data security
  • Meta data integration
  • Minimise data inconsistency
  • improve data access
  • improve decision making and end user productivity
• Solves File based systems limitations

• Data is stored in files
• Each file has a specific format
• Programs that use these files depend on knowledge about that format

• No standards
• Data duplication
• Dependencies
• Data inconsistencies
• Limited sharing
• No way to generate ADHOC queries
• No prevision for security, recovery, concurrency

• A data model is a collection of concepts for describing data
• A schema is a description of a particular collection of data using a given data model
• The relational model of data is the most widely used model today
  • Main concept: Relation, basically a table with rows and columns
  • Every relation has a schema, which describes the columns or fields

• Many views, single conceptual (logical) schema and physical schema.
• Schemas are defined using Data Definition Language (DDL)
• Data is modified using Data Manipulation Language (DML)

• What application programs see; views can also hide information(such as an instructor’s salary) for security purposes
• Different users will see different information depending on what they are logged in as and what view has been selected for that user

• How the data is actually stored and structured
• Based on the data model used
• Like a blueprint of the data

• Describes how a recorded is stored
• Actual location of the data

• Hierarchical Model
  • First to be introduced
  • Stores data in a hierarchical data structure
  • Starts at the root and branches down into children
• Network Model
  • Extension of a hierarchical model
  • Same as the Hierarchical model apart from a few things
  • A child can have more than one parent
  • Replaces the hierarchical tree with a graph
• Relational Model
  • Most widely used model now
  • 2 dimensional table
  • All information stored in rows and columns
• Object-oriented Data model
  • Data and relationship are stored in one object
  • Can store audio video images.
• Entity-relationship model
  • High level data model diagram
  • Real world problem is viewed in pictorial form
  • Easy to understand
• NoSQL
  • Not only SQL
  • Provides a flexible schema for the storage, retrieval of data beyond the typical table data structure found in the normal data base structures
  • Most companies use NoSQL as a data model

• MongoDB - NoSQL
• MySQL - Relational Model
• Oracle Database - Object-oriented data model
• PostgreSQL - Relational Model

Put Notes Here

• Lecture 1