Logical Models

Describe what a system is or does. Are independent of technical

implementation.Depict business requirements.Are good for communicating with end

users.Examples: Data, process and object

models.

Data Modeling

A technique for organizing and documenting a system’s data.

Sometimes called database modeling or information modeling.

The basic tool for data modeling is called an entity-relationship diagram (ERD).

Entity Relationship Diagrams (ERDs)

Three basic elements: Entity types - the kinds of things the

information system collects information about.

Relationship - the way an entity type is associated with another.

Attributes - specific information about an entity type.

ERDs

Professor

Professor

Course

Section Student

Section

Section

Office

Is registered in

Has

Has

Teaches

Types of relationships in entity-relationship

Source: Alter S. (1999), Information Systems: A Management Perspective, Third Edition

One-to-one relationship

One-to-many relationship

Optional one-to-many relationship

Many-to-many relationship

Entity Relationship Diagram

Belongs to

Department

StudentSectionProfessor

Course

Office

Offers

Has

TeachesIs registered in

Has

Entity - Relationship Diagram for part of a university registration system

Source: Alter S. (1999), Information Systems: A Management Perspective, Third Edition

Process Modeling

A technique for organizing and documenting the structure and flow of data through a

system’s processes and/or the logic, policies, and procedures to be

implemented by a system’s processes. (Whitten and Bentley 1998)

Tools: data flow diagrams (DFD) and IDEF0

Data Flow Diagrams (DFDs)

Four basic symbols: Process - transforms inputs into outputs.

External entity - any person or organization that provides data to a process in the system or receives data from a process.

Process

External Entity

Data Flow Diagrams (DFDs)

Data store - a location where data is stored.

Data flow - represents movement of data between processes, data stores and external entities.

Data Store

Data Flow

Creating DFDs

Starting point is a context diagram, which verifies the scope of the system by showing the sources and destinations of data used and generated by the system.

System represented as a single process is at the center of the context diagram.

Surrounding that process are external entities and external data stores.

Creating DFDs (contd.)

The business process in the context diagram is broken into its constituent processes to describe exactly how work is done.

These constituent processes along with the data stores, external entities and data flows constitute the top level data flow diagram.

Creating DFDs (contd.)

Constituent processes can be broken into sub-processes.

DFDs make it possible to look at business processes at any level of detail.

In addition to the context diagram, one or more DFDs are developed based on the level of detail required.

Purchasing system - Context diagram

Invoice

Material

PlanningDepartment

ReceivingDepartment

PURCHASINGSYSTEM

Supplier

Material requirement

Confirmation of receipt

Order

Payment

Context diagram for the Ford purchasing systemSource: Alter S. (1999), Information Systems: A Management Perspective, Third Edition

Purchasing System - Data Flow Diagram

Material requirement

Purchase order

Receipt details

Purchase order details

Material Planning Department

Receiving Department

SupplierPurchase Orders

Receipt Confirmations

Order material

Decide what to pay

Pay the supplier

PCH 1

PCH 2

PCH 3

Purchase order

Invoice

Payment

Receipt confirmation

Data flow diagram showing the main processes in Ford’s original purchasing systemSource: Alter S. (1999), Information Systems: A Management Perspective, Third Edition

Payment authorization

Integration Definition for Function (IDEF)

Background

Integrated Computer Aided Manufacturing (ICAM) program in US Air Force developed the IDEF series of techniques to improve manufacturing productivity.

IDEF0 - Function model, IDEF1 - Information model, IDEF2 - Dynamic model.

IDEF techniques widely used in government/industrial sectors.

IDEF0 Concepts

Technique for performing and managing needs analysis, benefits analysis, requirements definition, functional analysis, and systems design.

Reflects how system functions interrelate and operate.

IDEF0 Semantics

Box - Function (Ex. Perform Inspection)Left arrow - Inputs (Ex. Design data)Top arrow - Controls (Ex. Design

requirements)Bottom arrow - Mechanisms (Ex. Design

Engineer)Right arrow - Output (Ex. Detailed design)

IDEF0 Semantics (contd.)

Input

Mechanism

Control

OutputDesign data

Engineer

Requirements

Detailed design

FUNCTIONDESIGN

IDEF0 Diagrams

IDEF0 models composed of: graphic diagrams, text, and glossary.

Boxes representing a function can be broken down or decomposed into more detailed diagrams.

Top level diagram in the model provides the most general description, with details provided in the lower levels.

Purchasing System - Context diagram

Material requirements

Confirmation of receipt

Invoice PURCHASING

SYSTEM

Purchase Order

Payment

Policies and procedures

Resources

Purchasing System - IDEF Diagram

ORDERMATERIAL

Material

requirements

Purchase order

DETERMINEPAYMENT

Receipt detailsInvoice

PAY THESUPPLIER

Payment authorization

Payment

Data Warehouses

Used for building the data management infrastructure for DSSs and EISs.

A database (or collection of databases) that is optimized for decision support.

Populated through the extraction and integration of data from both operational and external data sources.

Warehouse Architecture

Three types of components the platform and software (including the

repository) that house the data warehouse,

the data acquisition software or back end, which extracts data, consolidates and summarizes the data, and loads the data into the data warehouse, and

the client or front end software, which allows users to access and analyze data.

Role of the Repository

Technical role - to support the building and maintenance of the data warehouse. document data sources and targets data transformation and cleanup rules interface to CASE tools document warehouse data model

Business-related role - to support end users in accessing and analyzing data.

Data Marts

Data stores specific to user-communities.

Examples are EIS server for executives DSS servers for departments

(marketing, finance, and manufacturing)Data is structured in the form of a

multi-dimensional database.

Multidimensional Analysis

An analytical technique that allows users to view data in a dimensional cube format.

Users can perform operations such as drill-down, roll-up, slice and dice, and data pivoting.

Another term for multidimensional analysis is on-line analytical processing (OLAP).

Multidimensional Database

Relational structure - data is stored in a tabular form and is not preprocessed. Slow performance is an issue.

Star structure - two types of tables are used, fact and dimension. A “virtual” cube representation.

Multidimensional database - preprocessed data stored in the form of arrays.

MOLAP and ROLAP

MOLAP is OLAP with a multidimensional database.

ROLAP or relational OLAP allows access to the data without building a specific multidimensional database.

MOLAP is suited for analysis on data marts in a multi-user environment.