MIS Bus system analysis exam

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kendall_sad9_pp_07-2.ppt

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Kendall & Kendall
Systems Analysis and Design, 9e

Using Data Flow Diagrams

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Learning Objectives

  • Comprehend the importance of using logical and physical data flow diagrams (DFDs) to graphically depict movement for humans and systems in an organization.
  • Create, use, and explode logical DFDs to capture and analyze the current system through parent and child levels.
  • Develop and explode logical DFDs that illustrate the proposed system.
  • Produce physical DFDs based on logical DFDs you have developed.
  • Understand and apply the concept of partitioning of physical DFDs.

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Data Flow Diagrams

  • Graphically characterize data processes and flows in a business system
  • Depict:
  • System inputs
  • Processes
  • Outputs

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A series of layered data flow diagrams may be used to represent and analyze detailed procedures in the larger system.

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Major Topics

  • Data flow diagram symbols
  • Data flow diagram levels
  • Creating data flow diagrams
  • Physical and logical data flow diagrams
  • Partitioning
  • Communicating using data flow diagrams

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Advantages of the Data Flow Approach

  • Freedom from committing to the technical implementation too early
  • Understanding of the interrelatedness of systems and subsystems
  • Communicating current system knowledge to users
  • Analysis of the proposed system

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Basic Symbols

  • A double square for an external entity
  • An arrow for movement of data from one point to another
  • A rectangle with rounded corners for the occurrence of a transforming process
  • An open-ended rectangle for a data store

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The Four Basic Symbols Used in Data Flow Diagrams, Their Meanings, and Examples
(Figure 7.1)

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An entire system and numerous subsystems can be depicted graphically with these four symbols in combination.

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External Entities

  • Represent another department, a business, a person, or a machine
  • A source or destination of data, outside the boundaries of the system
  • Should be named with a noun

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An external entity (outside the boundaries of the system) sends data to (source) or receives data from (destination) the system.

Each entity is labeled with a name, generally a noun.

The same entity may be used more than once on a given data flow diagram.

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Data Flow

  • Shows movement of data from one point to another
  • Described with a noun
  • Arrowhead indicates the flow direction
  • Represents data about a person, place, or thing

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Data flows occurring simultaneously can be depicted doing just that through the use of parallel arrows.

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Process

  • Denotes a change in or transformation of data
  • Represents work being performed in the system
  • Naming convention:
  • Assign the name of the whole system when naming a high-level process
  • To name a major subsystem attach the word subsystem to the name
  • Use the form verb-adjective-noun for detailed processes

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The data flow leaving a process is always labeled differently then the data flow entering the process.

A process must also be given a unique identifying number indicating its level in the diagram.

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Data Store

  • A depository for data that allows examination, addition, and retrieval of data
  • Named with a noun, describing the data
  • Data stores are usually given a unique reference number, such as D1, D2, D3
  • Represents a:
  • Database
  • Computerized file
  • Filing cabinet

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Data stores represent a person, place, or thing which is why they are named with a noun.

Temporary data stores, such as scratch paper or a temporary computer file are not included on the data flow diagram.

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Steps in Developing Data Flow Diagrams

(Figure 7.2)

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Data flow diagrams can and should be drawn systematically.

To begin a data flow diagram, collapse the organization’s system narrative into a list with four categories of external entity, data flow, process, and data store. This list helps determine the boundaries of the system. Next begin drawing the context diagram.

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Creating the Context Diagram

  • The highest level in a data flow diagram
  • Contains only one process, representing the entire system
  • The process is given the number 0
  • All external entities, as well as major data flows are shown

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Basically the context diagram consists of:

  • one process—depicting the entire system
  • external entities
  • data flows from the external entities to the process

The diagram does not contain any data stores.

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Basic Rules

  • The data flow diagram must have one process
  • Must not be any freestanding objects
  • A process must have both an input and output data flow
  • A data store must be connected to at least one process
  • External entities should not be connected to one another

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Context Diagram (Figure 7.3)

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Drawing Diagram 0

  • The explosion of the context diagram
  • May include up to nine processes
  • Each process is numbered
  • Major data stores and all external entities are included

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Including more than nine processes will result in a cluttered diagram that is difficult to understand.

Each process is numbered with an integer, starting form the upper left-hand corner and working toward the lower right-hand corner.

Because a data flow diagram is two-dimensional, you can start at any point and work forward or backward through the diagram.

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Drawing Diagram 0 (continued)

  • Start with the data flow from an entity on the input side
  • Work backward from an output data flow
  • Examine the data flow to or from a data store
  • Analyze a well-defined process
  • Take note of any fuzzy areas

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Because a data flow diagram is two-dimensional, you can start at any point and work forward or backward through the diagram.

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Note Greater Detail in Diagram 0
(Figure 7.3)

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Data Flow Diagram Levels

  • Data flow diagrams are built in layers
  • The top level is the context level
  • Each process may explode to a lower level
  • The lower level diagram number is the same as the parent process number
  • Processes that do not create a child diagram are called primitive

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Creating Child Diagrams

  • Each process on diagram 0 may be exploded to create a child diagram
  • A child diagram cannot produce output or receive input that the parent process does not also produce or receive
  • The child process is given the same number as the parent process
  • Process 3 would explode to Diagram 3

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The process on Diagram 0 that is exploded is called the parent process, and the diagram that results is called the child diagram.

On Diagram 3, the processes would be numbered 3.1, 3.2, 3.3, and so on. This allows the analyst to trace a series of processes through many levels of explosion.

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Creating Child Diagrams (continued)

  • Entities are usually not shown on the child diagrams below Diagram 0
  • If the parent process has data flow connecting to a data store, the child diagram may include the data store as well
  • When a process is not exploded, it is called a primitive process

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In addition, the lower-level diagram may contain data stores not shown on the parent process.

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Differences between the Parent Diagram (above) and the Child Diagram (below) (Figure 7.4)

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Data Flow Diagrams Error Summary

  • Forgetting to include a data flow or pointing an arrow in the wrong direction
  • Connecting data stores and external entities directly to each other
  • Incorrectly labeling processes or data flow

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Data Flow Diagrams Error Summary (continued)

  • Including more than nine processes on a data flow diagram
  • Omitting data flow
  • Creating unbalanced decomposition (or explosion) in child diagrams

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Checking the Diagrams for Errors (Figure 7.5)

  • Forgetting to include a data flow or pointing an arrow in the wrong direction

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Checking the Diagrams for Errors (continued Figure 7.5)

  • Connecting data stores and external entities directly to each other

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Typical Errors that Can Occur in a Data Flow Diagram (Payroll Example) (continued Figure 7.5)

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Logical and Physical Data Flow Diagrams

  • Logical
  • Focuses on the business and how the business operates
  • Not concerned with how the system will be constructed
  • Describes the business events that take place and the data required and produced by each event

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Logical and Physical Data Flow Diagrams

  • Physical
  • Shows how the system will be implemented
  • Depicts the system

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Features Common of Logical and Physical Data Flow Diagrams (Figure 7.7)

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The Progression of Models from Logical to Physical (Figure 7.8)

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The progression of creating data flow diagrams is:

  • Analyze the current system (current logical DFD).
  • Add features the new system should include (the proposed logical DFD).
  • Finally the best methods for implementing the new system should be developed (the physical DFD).

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Logical Data Flow Diagram Example (Figure 7.9)

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Physical Data Flow Diagram Example (Figure 7.9)

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Developing Logical Data Flow Diagrams

  • Better communication with users
  • More stable systems
  • Better understanding of the business by analysts
  • Flexibility and maintenance
  • Elimination of redundancy and easier creation of the physical model

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Better communication with users—centered on business activities.

More stable systems—based on business events and not on a particular technology or method of implementation.

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Developing Physical Data Flow Diagrams

  • Clarifying which processes are performed by humans and which are automated
  • Describing processes in more detail
  • Sequencing processes that have to be done in a particular order
  • Identifying temporary data stores
  • Specifying actual names of files and printouts
  • Adding controls to ensure the processes are done properly

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Physical Data Flow Diagrams Contain Many Items Not Found in Logical Data Flow Diagrams (Figure 7.10)

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Physical data flow diagrams are often more complex than logical data flow diagrams simply because of the many data stores present in the system.

The acronym CRUD is used for Create, Read, Update, and Delete.

A CRUD matrix shows which programs or processes add, read, update, or delete master file records.

Intermediate data stores—consist of transaction files used to store data between processes.

A physical data flow diagram may appear more linear that a logical model.

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CRUD Matrix

  • The acronym CRUD is often used for
  • Create
  • Read
  • Update
  • Delete
  • These are the activities that must be present in a system for each master file
  • A CRUD matrix is a tool to represent where each of these processes occurs in a system

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CRUD Matrix (Figure 7.11)

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Event Modeling and Data Flow Diagrams

  • An input flow from an external entity is sometimes called a trigger because it starts the activities of a process
  • Events cause the system to do something and act as a trigger to the system
  • An approach to creating physical data flow diagrams is to create a data flow diagram fragment for each unique system event

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Triggers start activities or processes, which in turn use data or produce output.

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Event Response Tables

  • An event table is used to create a data flow diagram by analyzing each event and the data used and produced by the event
  • Every row in an event table represents a data flow diagram fragment and is used to create a single process on a data flow diagram

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An Event Response Table for an Internet Storefront (Figure 7.12)

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Data Flow Diagrams for the First Three Rows of the Internet Storefront Event Response Table (Figure 7.13)

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  • A dataflow diagram fragment is represented by one row in the table.
  • Each DFD fragment is a single process on a data flow diagram.
  • All the fragments are then combined to form Diagram 0.
  • The trigger and response column becomes the input and output data flows.
  • The activity becomes the process.
  • The data stores are determined by examining the input and output data flows.

The advantage of building data flow diagrams based on events is that the users are familiar with the events that take place in their business area and know how the events drive other activities.

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Use Cases and Data Flow Diagrams

  • Each use case defines one activity and its trigger, input, and output
  • Allows the analyst to work with users to understand the nature of the processes and activities and then create a single data flow diagram fragment

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Partitioning Data Flow Diagrams

  • Partitioning is the process of examining a data flow diagram and determining how it should be divided into collections of manual procedures and computer programs
  • A dashed line is drawn around a process or group of processes that should be placed in a single computer program

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Analyze each process to determine whether it should be a manual or automated procedure.

Group automated procedures into a series of computer programs.

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Reasons for Partitioning

  • Different user groups
  • Timing
  • Similar tasks
  • Efficiency
  • Consistency of data
  • Security

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Different user groups—are the processes performed by several different user groups, often at different physical locations in the company? If so, they should be partitioned into different computer programs.

  • Timing—processes that execute at different times must be in separate programs
  • Similar tasks—may be included in the same program.
  • Efficiency—several batch processes may be included in the same program for efficiency.
  • Consistency—several processes may be included in the same program or job stream for consistency of data.
  • Security—may be partitioned into different programs for security reasons.

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Partitioning Websites

  • Improves the way humans use the site
  • Improves speed of processing
  • Ease of maintaining the site
  • Keep the transaction secure

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Each time data must be obtained from a data store or an external partner, a website designer might consider creating a unique Web form and DFD process to validate and process the data or may also use Ajax, sending a request to the server and obtain a small amount of data or an XML document returned to the same page.

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Communicating Using
Data Flow Diagrams

  • Use unexploded data flow diagrams early when ascertaining information requirements
  • Meaningful labels for all data components

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Use unexploded data flow diagrams early when ascertaining information requirements—at this stage they can provide an overview of data movement through the system, lending a visual perspective unavailable in narrative data.

Meaningful labels for all data components—labels should not be generic.

Data flow diagrams can be used for documenting high and low levels of analysis and helping to substantiate the logic underlying the data flows of the organizations.

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Summary

  • Data flow diagrams
  • Structured analysis and design tools that allow the analyst to comprehend the system and subsystems visually as a set of interrelated data flows
  • DFD symbols
  • Rounded rectangle
  • Double square
  • An arrow
  • Open-ended rectangle

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Summary (continued)

  • Creating the logical DFD
  • Context-level data flow diagram
  • Level 0 logical data flow diagram
  • Child diagrams
  • Creating the physical DFD
  • Create from the logical data flow diagram
  • Partitioned to facilitate programming

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Summary (continued)

  • Partitioning data flow diagrams
  • Whether processes are performed by different user groups
  • Processes execute at the same time
  • Processes perform similar tasks
  • Batch processes can be combined for efficiency of data
  • Processes may be partitioned into different programs for security reasons

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