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Chapter7 Using Dataflow Diagrams

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1) Learning Objectives

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• 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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2) Data Flow Diagrams

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

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3) Advantages of the Data Flow Approach

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• 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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4) External Entities

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• 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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5) Data Flow

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• 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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6) Process

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• 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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7) Creating the Context Diagram

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• 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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8) Basic Rules

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• 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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9) Data Flow Diagram Levels

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• 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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10) Creating Child Diagrams

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• 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. • 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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11) Logical and Physical Data Flow Diagrams

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

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

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13) Developing Logical Data Flow Diagrams

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• 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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14) Developing Physical Data Flow Diagrams

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• 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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16) Event Modeling and Data Flow Diagrams

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• 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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17) Event Response Tables

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• 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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18) Use Cases and Data Flow Diagrams

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• 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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CHAPTER8 Analyzing Systems Using Data Dictionaries

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19) Learning Objectives

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• Understand analysts use of data dictionaries for analyzing data-oriented systems. • Create data dictionary entries for data processes, stores, flows, structures, and logical and physical elements of the systems being studied, based on DFDs. • Understand the concept of a repository for analysts' project information and the role of CASE tools in creating them. • Recognize the functions of data dictionaries in helping users update and maintain information systems.

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20) Cataloging

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• Data flow diagrams can be used to catalog: • Data processes • Flows • Stores • Structures • Elements • Cataloging takes place with the data dictionary

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21) The Data Dictionary

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• A reference work of data about data (metadata) • Collects and coordinates data terms, and confirms what each term means to different people in the organization

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22) Need for Understanding the Data Dictionary

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• Provide documentation. • Eliminate redundancy. • Validate the data flow diagram. • Provide a starting point for developing screens and reports. • Determine the contents of data stored in files. • To develop the logic for DFD processes. • Create XML.

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23) The Data Repository

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• A data repository is a large collection of project information. • It includes: • Information about the data maintained by the system • Procedural logic and use cases • Screen and report design • Data relationships • Project requirements and final system deliverables • Project management information

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24) Defining the Data Flow

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• ID—identification number • Unique descriptive name • A general description of the data flow • The source of the data flow • The destination of the data flow • Type of data flow • The name of the data structure describing the elements • The volume per unit time • An area for further comments and notations

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25) Describing Data Structures

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• Data structures are made up of smaller structures and elements. • An algebraic notation is used to describe data structures.

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26) Logical and Physical Data Structures

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• Logical: • Show what data the business needs for its day-to-day operations. • Physical: • Include additional elements necessary for implementing the system.

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27) Physical Data Structures

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• Key fields used to locate records • Codes to identify record status • Transaction codes to identify different record types • Repeating group entries • Limits on items in a repeating group • Password

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28) Creating the Data Dictionary

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• Data dictionary entries • Created after the data flow diagram is completed or • Created as the data flow diagram is being developed • Created using a top-down approach

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CHAPTER9 Process Specifications and Structured Decisions

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29) Learning Objectives

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• Understand the purpose of process specifications. • Recognize the difference between structured and semistructured decisions. • Use structured English, decision tables, and decision trees to analyze, describe, and document structured decisions. • Choose an appropriate decision analysis method for analyzing structured decisions and creating process specifications.

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30) Logic of Decisions

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• Documenting and analyzing logic: • Structured English • Decision tables • Decision trees • Logic and structured decisions are distinguishable from semistructured decisions. • Structured decision analysis methods promote completeness, accuracy, and communication.

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31) Goals of Producing Process Specifications

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• Reduce process ambiguity. • Obtain a precise description of what is accomplished. • Validate the system design.

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32) How Process Specifications Relate to the Data Flow Diagram (Figure 9.1)

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33) Process Specification Format Information

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• The process number • The process name • Description of what the process accomplishes • A list of input data flow • Output data flows • Type of process • Uses prewritten code • Process logic description • Logic method reference • List any unresolved issues

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34) The Process Number

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• Must match the process ID on the data flow diagram • Allows the analyst to work on or review any process, and to locate the data flow diagram containing the process easily

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35) The Process Name

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• The same as displays within the process symbol on the DFD

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36) Description of What the Process Accomplishes

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• Example: Determine if an item is available for sale. If it is not available, create a backordered item record. Determine the quantity available.

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37) Output Data Flows

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• Uses data flow diagram and data dictionary names

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38) Type of Process

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• Batch • Online • Require screen designs • Manual • Should have well-defined procedures for employees performing the process tasks

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39) Uses Prewritten Code

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Include the name of the subprogram or function containing the code.

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40) Process Logic Description

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• This should state policy and business rules, not computer language pseudocode • Business rules are the procedures that allow a corporation to run its business.

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41) Logic Method Reference • If there is not enough room for a complete

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• If there is not enough room for a complete structured English description include a reference to the structured English description, decision table, or tree depicting the logic.

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42) List Any Unresolved Issues

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• Incomplete portions of logic • These issues form the basis of the questions used for follow-up interviews with users or business experts you have added to your project team

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43) Structured English

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• Used when the process logic involves formulas or iteration, or when structured decisions are not complex • Based on structured logic and simple English statements such as add, multiply, and move

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44) Writing Structured English

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• Express all logic in terms of sequential structures, decision structures, case structures, or iterations. • Use and capitalize accepted keywords such as IF, THEN, ELSE, DO, and PERFORM. • Indent blocks of statements to show their hierarchy (nesting) clearly. • Underline words or phrases that have been defined in a data dictionary. • Clarify the logical statements.

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45) Advantages of Structured English

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• Clarifying the logic and relationships found in human languages • An effective communication tool, it can be taught to and understood by users in the organization

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