Information Systems: Week 1 and 2

Managing Systems

• Disintermediation: The removing of intermediaries.

History of Databases 

• Precise business records = sheep + goat tallies, book keeping.

Data, Information and Knowledge

• Data: Streams unorganised raw facts.
• Information: Data structured give meaning.
• Knowledge: Data + Info been organised understanding, experience + application (Turban, 2008).

Information Systems as Transactional Processing Systems 

• TPS perform + record daily routine transactions necessary conduct business.
• Typically single purpose applications (e.g. payroll, sales order entry).

TPS Inputs: Internal

• Orders shipped + Employee time sheets

TPS Inputs: External

• Orders + Payments

TPS Outputs: Internal

• Packing notes + Staff rosters

TPS Outputs: External

• Dispatch email + Website updates

Information Systems as Management Information Systems

• Systems provide info management.
• Typically hybrid applications, (e.g. process control systems + HRM systems).

The Role of the Database

• Databases (DBMS) are heart every info system - all hold + manipulate data.
• Databases hold data structured way, so can searched + calculated.
• Several designs of DBMS - some common ones: hierarchial, network + object-oriented.

Data Analysis

• Discovers + presents data arising Requirements.
• Requirement analysis: e.g. when click logo website, take me back home page.

Things used to Identify and Fix Redundant Data

• Update Anomalies
• Delete Anomalies 
• Insert Anomalies

Types of Anomalies 

• Update Anomalies: Update anomaly exists 1/+ instances duplicated data updated.
• Delete Anomalies: Delete anomaly exists certain attributes lost because deletion other attributes.
• Insert Anomalies: Insert anomaly occurs certain attributes cannot inserted into database without presence other attributes.

The Process of Normalisation 

• Normalisation data analysis technique design database system.
• Allows database designer understand current data structures in organisation.
• End result normalisation set entities which removes unnecessary redundancy (i.e. duplication data).

Normalisation Stages

• Process involves applying series tests relation determine whether satisfies/violates requirements given normal form.
• When test fails = relation decomposed simpler relations individually meet normalisation tests. 
• 3 Normal forms: 1NF, 2NF + 3NF initially proposed Ted Codd.

Entity Relationship Diagrams (ERD)

• AKS: Logical data structures
• Diagrammatic overview database structure

Factors Involved

• Entities: Any object which info needs held system

Attributes (Data items, fields):

• Each item info belonging entity
• Not normally shown ERD

• Symbols: ERD typically uses rectangle display entity shape, depends methodology.

Relationships between Entities

Relationships 

• Entities within system related other entities.
• On ERD, relationship shown by line + typically labelled both directions.

Degree: The 3 types

• One-to-one (1:1)
• One-to-many (1:n)
• Many-to-many (m:n)

Degree of Relationships 

• Degree of relationship between entities shown using 'crow's feet' relational line.