Transcript Appendix A - Gadjah Mada University

MANAGEMENT INFORMATION SYSTEMS 8/E
Raymond McLeod, Jr. and George Schell
Appendix A
Data Modeling
Copyright 2001 Prentice-Hall, Inc.
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Data and Process Modeling

During systems development both processes
and data must be modeled
– Data modeling describes data used by system
– Process modeling describes processes carried
out by system

Level of detail
– Varies between highest summary and lowest
detail
– Structured tools enable level of detail to be
varied
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Entity-Relationship Diagram
(ERD)
Documents firm’s data by identifying types
of data entities and their interrelationships
 Prepared at “big picture” point of data
specification
 Very flexible

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Entity Types
Environmental
 Resource
 Important transaction

Entity
symbol
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Relationship
An association between two entity types
Relationship
symbol
Employee
Fills out
Time card
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Connectivity
Time card
1
Number of times an entity occurs
in relation to another entity
Produces
1
Payroll
check
A. One to one
Dosen
1
Sebagai dosen M Mahasiswa
wali
M
M
B. One to many
Mahasiswa
Mengambil
Matakuliah
C. Many to many
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Attributes
Characteristics of an entity
 Actually data elements
 Identifiers are unique attributes of the entity
 Descriptors describe the entity

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Preparation of an EntityRelationship Diagram
1. Identify the entities
2. Identify the relationships
3. Prepare a rough ERD
4. Map data elements to the entities
5. Perform a data analysis (through third normal
form is common)
6. Prepare a modified ERD
7. Review the ERD with users and refine
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Rough ERD
Supplier
Supplier number
1
Fills
M
Purchase
order number
Purchase
order
M
Contains
M
Raw
Material
M
Represents
Item number
1
Supplier number
Accounts
payable
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Normalization

First normal form (1NF)
– Eliminate repeating elements in an entity

Second normal form (2NF)
– Ensure that descriptor attributes rely on the
entire composite key for the assignment of
values

Third normal form (3NF)
– Ensure that an attribute value cannot be
determined by values of other attributes
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Supplier number
Supplier name
Supplier address
1
Purchase order number
Purchase order date
Fills
Supplier number
Supplier name
M
Supplier address
Item number (n times)
Purchase
Item description (n times)
order
Item quantity (n times)
Item unit price (n times)
M
Item extended price (n time)
Purchase order amount
Represents
Supplier number
Supplier name
Supplier address
Total accounts payable
Data Elements
are Mapped
Supplier
1
Accounts
payable
M
Contains
M
Raw
Material
Item number
Item description
Warehouse location
Item unit price
Balance on hand
Reorder point
Order quantity
Quantity on hand
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Normalized Portion of ERD
PURCHASE
ORDER
1
M
CONTAINS
PURCHASE ORDER
NUMBER
Purchase order date
Supplier number
Supplier
Supplier address
Purchase order amount
PURCHASE
ORDER
LINE
1
1
REPRESENTS
PURCHASE ORDER NUMBER
ITEM NUMBER
Item number
Item description
Item quantity ordered
Item unit price
Item extended price
RAW
MATERIAL
LINE/ITEM NUMBER
Item description
Warehouse
location
Item unit price
Balance on hand
Recorder point
Order quantity
Quantity on order
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Data Dictionary
Written description of the data contained in
the database
 First ones maintained in hardcopy form
 Most are now maintained on a computer
 Data flow dictionary entry describes data
flows on DFD

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Data Dictionary [cont.]
Data store dictionary entry describes unique
data stored in a DFD
 Data structure dictionary entry is completed
for each structure listed on the data store
and data flow forms
 Data element dictionary entry is used for
each data element, or attribute included in
all of the structures

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Data Flow Dictionary Entry
Data flow name:
Sales Order
Description:
The documents that are filled
out by customers to identify
the products, and the
quantities of each, that they
will wish to purchase.
From:
1. Open mail
To:
information
2. Enter sales order
Data structures:
Sales order record
Comments:
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Data Store Dictionary Entry
Data store name:
Sales order form
Description:
The history file of sales order forms, after
the data has been entered into the sales
commission system.
Data structures:
Sales order record
Volume:
Approximately 140 per day
Activity:
Access:
Order department personnel
Comments:
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Data Structure Dictionary Entry
Structure name:Sales order record
Description:
The sales order form that the customer uses to
order merchandise.
Date elements: Customer.Number
Customer.Order.Number
Salesperson.Number
Customer.Order.Date
*Item.Number
*Item.Description
*Item.Quantity
*Item.Unit.Price
*Item.Extended.Price
Comments:
Elements marked with asterisks occur for each
item record
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Data Element Dictionary Entry
Data element name:
Salesperson.Number
Description:
The number that identifies the salesperson
Type:
Numeric
Length:
4
No. decimal pos.
Aliases:
Salesman number, Sales rep number
Range of values:
0001-9999
Typical value:
Specific values:
Other editing details:
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Summary
During early years of computing, emphasis
was on the processes performed.
 Currently, emphasis is on data
 ERDs are a primary tool in data analysis
 Data dictionaries provide a means of
documenting data

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