Chp5 hw2

Chapter 5Data and Process Modeling
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Describe data and process modeling
concepts and tools, including data flow
diagrams, a data dictionary, and process
descriptions
• Describe the symbols used in data flow
diagrams and explain the rules for their use
• Draw data flow diagrams in a sequence,
from general to specific
•
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Explain how to level and balance a set of
data flow diagrams
• Describe how a data dictionary is used and
what it contains
• Use process description tools, including
structured English, decision tables, and
decision trees
• Describe the relationship between logical
and physical models
•
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Logical Model: Shows what the system must
do, regardless of how it will be
implemented physically
• Physical Model: Describes how the system
will be constructed
•
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Systems analysts use graphical techniques
to describe an information system
• Data flow diagram (DFD) – Uses various
symbols to show how the system
transforms input data into useful
information
•
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A data flow diagram (DFD) shows how data
moves through an information system but
does not show program logic or processing
steps
• A set of DFDs provides a logical model that
shows what the system does, not how it
does it
•
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 DFD Symbols
◦ Four basic symbols represent processes, data flows,
data stores, and entities
◦ Gane and Sarson: Used in data
flow diagrams
 Processes, data flows,
data stores, and external
entities all have a unique symbol
◦ Yourdon: Used in data flow
FIGURE 5-1 Data flow diagram symbols, symbol names, and
diagrams
examples of the Gane and Sarson and Yourdon symbol sets
 Processes, data flows, data stores, and external entities each
have a unique symbol
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Process Symbol
• Must have at least one input
and at least one output
• Contains business logic that
transforms the data
• Process name identifies its
function (verb)
• Examples” : “apply rent
payment” or “calculate
commission
• In DFDs, a process symbol
can be referred to as a black
box
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 Data Flow Symbol
◦ Represents one or more
data items
◦ The symbol for a data
flow is a line with a single
or double arrowhead
FIGURE 5-3 Examples of correct combinations of data flow and process symbols
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 Data Flow Symbol
◦ Following data flow and process combinations must
be avoided
◦ Spontaneous generation
◦ Black holes
◦ Gray holes
FIGURE 5-4 Examples of incorrect combinations of data flow and process symbols. APPLY
INSURANCE PREMIUM has no input and is called a spontaneous generation process.
CALCULATE GROSS PAY has no outputs and is called a black hole process. CALCULATE
GRADE has an input that is obviously unable to produce the output. This process is called
a gray hole
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Data Store symbol
• Represent data that the system
stores
•
•
A DFD does not show the detailed
contents of a data store — the specific
structure and data elements are defined
in the data dictionary
A data store must be connected to a
process with a data flow
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FIGURE 5-6 Examples of incorrect
uses of data store symbols: Two data
stores cannot be connected by a data
flow without an intervening process,
and each data store should have an
outgoing and incoming data flow
FIGURE 5-5 Examples of correct
uses of data store symbols in a data
flow diagram
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Entity Symbol
• Shows how the system interfaces
with the outside world
• A DFD shows only external entities
that provide data to the system or
receive output from the system
• DFD entities also are called
terminators because they are data
origins or final destinations
• Each entity must be connected to a
process by a data flow
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FIGURE 5-8 Examples of incorrect
uses of external entities. An external
entity must be connected by a data
flow to a process, and not directly to a
data store or to another external entity
FIGURE 5-7 Examples of correct uses of
external entities in a data flow diagram
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•
Keep in mind:
o All flow lines must
be labeled
o Large processes can
be broken down
into smaller
components
FIGURE 5-9 Examples of correct and
incorrect uses of data flows
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 Create a graphical model of the information
system based on your fact-finding results
◦ First, you will review a set of guidelines for
drawing DFDs
◦ Then you will learn how to apply these guidelines
and create a set of DFDs using a three-step
process
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 Guidelines for Drawing DFDs
◦ Draw the context diagram so that it fits on one page
◦ Use the name of the information system as the
process name in the context diagram
◦ Use unique names within each set of symbols
◦ Do not cross lines
◦ Provide a unique name and reference number for
each process
◦ Ensure that the model is accurate, easy to
understand, and meets the needs of its users
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FIGURE 5-10 Context
diagram DFD for grading
system
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 Step 1: Draw a
Context
Diagram
FIGURE 5-11 Context diagram DFD
for an order system
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 Step 2: Draw a
Diagram 0 DFD
◦ If same data flows in
both directions, you can
use a double-headed
arrow
◦ Diagram 0 is an
exploded view of
process 0
◦ Parent diagram
◦ Child diagram
◦ Functional primitive
FIGURE 5-13 Diagram 0 DFD for the order system
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 Step 3: Draw the
Lower Level
Diagrams
FIGURE 5-14 Diagram 1
DFD shows details of the
FILLORDER process in the
order system
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 Must use leveling
and balancing
techniques
 Leveling examples
◦ Uses a series of
increasingly detailed
DFDs to describe an
information
system
◦ Exploding,
partitioning, or
decomposing
FIGURE 5-15 This diagram does
not show the symbols that connect
to data flows entering or leaving
FILL ORDER on the context
diagram
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FIGURE 5-16 The order system diagram 0 is
shown at the top of the figure, and exploded
diagram 3 DFD (for the APPLY PAYMENT
process) is shown at the bottom. The two DFDs
are balanced because the child diagram at the
bottom has the same input and output flows as
the parent process 3 shown at the top
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FIGURE 5-17 Example of a parent
DFD diagram, showing process 0 as a
black box
FIGURE 5-18 In the next level of detail,
the process 0 black box reveals three
processes, two data stores, and four
internal data flows — all of which are
shown inside the dashed line
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A data dictionary, or data repository, is a
central storehouse of information about a
system’s data
• An analyst uses the data dictionary to
collect, document, and organize specific
facts about a system
• Defines and describes all data elements and
meaningful combinations of data elements
•
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 Data element: Smallest piece of data that
has meaning within an information system
◦ Called data item or field
◦ Are combined into records, also called data
structures
 Record: Meaningful combination of related
data elements that is included in a data flow
or retained in a data store
◦ Called data structures
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 Using CASE Tools for Documentation
◦ More complex the system, more difficult it is to
maintain full and accurate documentation
◦ Modern CASE tools simplify the task
◦ A CASE repository ensures data consistency
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 Documenting the Data Elements
◦ Every data element in the data dictionary should be
documented
◦ Objective – To provide clear, comprehensive
information about the data and processes that make
up a system
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 Documenting the Data
Elements
◦ Data element name and label
◦ Alias
◦ Type and length
◦ Default value
◦ Acceptable values – Domain
and validity rules
◦ Source
◦ Security
◦ Responsible user(s)
◦ Description and comments
Source: Visible Systems Corporation.
FIGURE 5-20 A Visible Analyst screen describes
the data element named SOCIAL SECURITY
NUMBER.
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 Documenting the Data Flows
◦ Data flow name or label
◦ Description
◦ Alternate name(s)
◦ Origin
◦ Destination
◦ Record
◦ Volume and frequency
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 Documenting the Data
Stores
◦ Data store name or label
◦ Description
◦ Alternate name(s)
◦ Attributes
◦ Volume and frequency
Source: Visible Systems Corporation.
FIGURE 5-21 Visible Analyst screen that documents a
data store named IN STOCK
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 Documenting the Processes
◦ Process name or label
◦ Description
◦ Process number
◦ Process description
FIGURE 5-22 Visible Analyst screen that describes a
process named VERIFY ORDER
Source: Visible Systems Corporation.
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 Documenting the Entities – Data dictionary
describes all external entities that interact
with the system
◦ Characteristics include
 Entity name
 Description
 Alternate name(s)
 Input data flows
 Output data flows
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 Documenting
the Records
◦ Record or data
structure name
◦ Definition or
description
◦ Alternate name(s)
◦ Attributes
Source: Visible Systems Corporation.
FIGURE 5-23 Visible Analyst screen that documents a
record, or data structure named CREDIT STATUS
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 Data Dictionary Reports – Following can be
obtained
◦ Alphabetized list of all data elements by name
◦ Report describing each data element and indicating
the user or department that is responsible for data
entry, updating, or deletion
◦ Report of all data flows and data stores that use a
particular data element
◦ Detailed reports showing all characteristics of data
elements, records, data flows, processes, or any
other selected item stored in the data
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 Process description: Documents the details of
a functional primitive and represents a specific
set of processing steps and business logic
 Tools – structured English, decision tables, and
decision trees
 Used in object-oriented development
◦ O-O analysis – combines data and the processes that
act on the data into things called objects, and similar
objects can be grouped together into classes
◦ O-O processes are called methods
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 Modular Design
◦ Based on
combinations of
three logical
structures,
sometimes called
control structures,
which serve as
building blocks for
the process
 Sequence
 Selection
 Iteration – looping
FIGURE 5-24 Sequence structure
FIGURE 5-25 Selection structure
FIGURE 5-26 Iteration
structure
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 Structured English
◦ Rules
 Use only the three building
blocks of sequence,
selection, and iteration
 Use indentation for
readability
 Use a limited vocabulary
 standard terms used in the
data dictionary
 Specific words that
describe the processing
rules
Source: Visible Systems Corporation.
FIGURE 5-27 The VERIFY ORDER process description
includes logical rules and a structured English version of
the policy. Notice the alignment and indentation of the
logic statements
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 Decision Tables
◦ Show a logical structure, with all possible
combinations of conditions and resulting actions
 Every possible outcome should be considered to
ensure that nothing has been overlooked
◦ Number of rules doubles each time a condition is
added
◦ Can have more than two possible outcomes
◦ Are the best way to describe a complex set of
conditions
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FIGURE 5-28 The Verify Order business process has two conditions. For an
order to be accepted, the product must be in stock and the customer must
have an acceptable credit status
FIGURE 5-29 Example of a simple decision table showing the processing logic of
the VERIFY ORDER process
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FIGURE 5-30 A third condition has been added to the Verify Order business process. For an order
to be accepted, the product must be in stock and the customer must have an acceptable credit
status. However, the credit manager now has the authority to waive the credit status requirement
FIGURE 5-31This table is based on the Verify Order conditions shown in Figure 5-30. With
three conditions, there are eight possible combinations, or rules
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FIGURE 5-32 In the first table, dashes have been added to indicate that a
condition is not relevant. In the second version, rules have been combined.
Notice that in final version, only four rules remain. These rules document the
logic, and will be transformed into program code when the system is developed
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FIGURE 5-33 A sales promotion policy with three conditions. Notice that the first statement contains
two separate conditions – one for the 5% discount, and another for the additional discount
FIGURE 5-34 This decision table is based on the sales promotion policy in
Figure 5-33. This is the initial version of the table, before simplification
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FIGURE 5-35 In this version, dashes have been added to indicate that a condition is not
relevant. At this point, it appears that several rules can be combined
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 Decision Trees
◦ Graphical representation of the conditions, actions,
and rules found in a decision table
◦ Show the logic structure in a horizontal form that
resembles a tree
◦ Provide the same results as decision tables, but in
different forms
FIGURE 5-36 This example is based on the same
Sales Promotion Policy shown in the decision tables
in Figures 5-34 and 5-35 on the previous page. Like
a decision table, a decision tree shows all
combinations of conditions and outcomes. The main
difference is the graphical format, which many
viewers find easier to interpret
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 While structured analysis tools are used to
develop a logical model for a new information
system, such tools also can be used to
develop physical models of an information
system
 A physical model shows how the system’s
requirements are implemented
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 Sequence of Models
◦ Systems analysts create a physical model of
the current system and then develop a logical
model of the current system before tackling a
logical model of the new system
 Performing extra step allows to understand the
current system better
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 Four-Model Approach
◦ Develop:
 A physical model of the current system
 A logical model of the current system
 A logical model of the new system
 A physical model of the new system
◦ Disadvantage – Additional time and cost
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 During data and process modeling, a systems
analyst develops graphical models to show
how the system transforms data into useful
information
 The end product of data and process
modeling is a logical model that will support
business operations and meet user needs
 Data and process modeling involves three
main tools: data flow diagrams, a data
dictionary, and process descriptions
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 Data flow diagrams (DFDs) graphically show
the movement and transformation of data in
the information system
 DFDs use four symbols
 A set of DFDs is like a pyramid with the
context diagram at the top
 The data dictionary is the central
documentation tool for structured analysis
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 Each functional primitive process is
documented using structured English,
decision tables, and decision trees
 Structured analysis tools can be used to
develop a logical model during one systems
analysis phase, and a physical model during
the systems design phase
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