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Management Information Systems

Prof. Payam Hanafizadeh, PhD

Allameh Tabataba'i University

2009

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Part2:Business Information Systems Development

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System Analysis

A system analyst looks at a phenomenon as a system, so s/he has to find out its essiential property and then figure out its components as subsystems.

System analysis makes it possible to understand problems and propose solutions.

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Fig1: The analysis and synthesis of a problem

Solution A

Sol.B

Sol.D

Sol. CSol.

ESol.

F

Complex Solution

Complex Problem

Problem A

Sub-Prob. CSub-Sub-

Prob. F

Sub-Sub-

Prob. E

Sub-Prob.

B

Sub-Prob.

D

Prob.A

Sub-

Prob. B

Sub-

Prob. D

Sub-

Prob. CSub-

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Prob. F

Sub-

Sub-

Prob. E

Sol. A

Sol.ESol.

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Sol.F

Sol.D

Sol.B Sol. A

Sol.

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Sol.

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Sol.

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Analysis

Pro

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m

Str

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IndividualSolutio

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Solution

Structured

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Synthesis

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Fig2: The Analysis Process Diagram

New System

ExistingSystem

Physical Model

Logical Model

Physical Model

Logical Model

Business Requirements

Tech

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Fig3-a: The four-step analysis process viewed as a cyclical process

- Understand current system

- Identify new requirement

s

- Specify new system solution

- Evaluate feasibility

4

3

1

2

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The iterative nature of the analysis process

The analysis is an iterative process.

The four steps which make a cyclical process can be iterated to gradually increase the analysts' understanding

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Fig3-b: The four-step analysis process viewed as a cyclical process

- Construct

existing physical model

- Construct existing

logical model

- Identify logical requirements- Identif

y physic

al reports

- Create new

logical model

- Create new

physical model

- Evaluate

feasibility

4

3

1

2

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Fig4: The iteration and layering inherent in the analysis

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A Logical Model

A logical model highlights the data content and handling, regardless of methods used to provide them.

Thus, the logical aspects of a system are those elements that are the same whether the work is done with pencils and paper or by a computer.

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A Physical Model

By contrast, a physical model tends to identify the aspects of the system that are dependent on:

- how the processing is currently or will be done- the people who are involved in the processing- the forms used- the computerized processing- and so on.

A model is not necessarily completely physical or compeletely logical.

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Table1: Summary of key differences between physical and logical models

Differencesgroup

Physical Logical

Viewpoint How processing is done? What the system does?

Processes Sequential Often parallel

Names Documents, people, forms Underlying data and process

Data flows Excess (tramp) dataOnly data used or produced by the process

ControlsIncludes controls for crossingman-machine boundary

Limited to essential business control

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Fig5-a: Logical model of an existing system

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Fig5-b: Logical model of an existing system- As modified by business requirements

Addprocess

Delete data

Add data

Delete

Add storage

Change data

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Fig5-c: Logical model of new system-derived from logical model of existing system and new business requirements

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Fig5-d: Physical model of new system-derived from logical model of new system and new physical (delivery oriented) requirements

On-line

Batch

Daily

Asneeded

Weekly

Man

Machine

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The combination of function (DFD) and data models in the Analysis Process

It is possible to define a data modeling process that can run in parallel with the construction of physical and logical models and can provide a higher quality new system physical model.

The existing physical data model, constructed in parallel with existing physical function model is simply the list of current physical files-both computer and manual- and their keys.

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The combination of function (DFD) and data models in the Analysis Process

This will concide with the collection of data store in the function model.

While deriving the logical (function) model for the existing system, also construct an E-R model that spans the existing system.

Next construction the logical data model for the new system. New business requirements may or may not derive the definition of new entities.

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The combination of function (DFD) and data models in the Analysis Process

But they will almost certainly dictate a change in the relationships and probably in the attributes.

You are now already to merge the two logical models – function and data – into a combined logical model for the new system.

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The combination of function (DFD) and data models in the Analysis Process

Do this by replacing the data stores that have been carried along in the function or data flow diagram – based models with the normalized set of data stores from the logical data model and adjusting data flows as necessary.

In practise, it is a good idea to do this merge using fairly low-level data flow diagram models, then create the intermediate-level parent diagrams.

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The combination of function (DFD) and data models in the Analysis Process

It is this merged logical model for the new system that can serve as the base for constructing the physical model for new system. One thing that happens during the construction of this physical model is the identification of the actual physical data bases to be used in new systems.

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Fig6: The combination of function (DFD) and data models in the Analysis Process

Merge

New System

ExistingSystem

Physical Model

Logical Model

Business Requirements

Tech

nic

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O

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Fu

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Part 2 References

[1]: Powers, Cheney, Crow, "Structured Systems Development, Analysis; Design, Implementation", 2nd edition, thompson international publishing, 1990.