SAD 2nd PPT
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This chapter discusses data and process modeling tools used during systems analysis, including data flow diagrams (DFDs), a data dictionary, and process descriptions. DFDs use symbols like processes, data flows, data stores, and entities to graphically represent how data moves through a system. A data dictionary centrally documents all data elements, data flows, processes, and other system components. Process descriptions explain the business logic and processing steps using structured tools like structured English, decision tables, and decision trees. The end goal of modeling is a logical model that shows what the system does at a high level without details of how it is implemented physically.
SAD 2nd PPT
- 1. Systems Analysis & Design 7th Edition Chapter 4 1
- 2. Chapter Objectives 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 Explain how to level and balance a set of data flow diagrams 2
- 3. Chapter Objectives 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 3
- 4. Introduction In chapter 4 & 5, you will develop a logical model of the proposed system and document the system requirements – Logical model shows what the system must do – Physical model describes how the system will be constructed 4
- 5. Overview of Data and Process Modeling Tools Systems analysts use many graphical techniques to describe an information system A data flow diagrams (DFD) uses various symbols to show how the system transforms input data into useful information 5
- 6. Data Flow Diagrams 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 6
- 7. Data Flow Diagrams • DFD Symbols 7
- 8. Data Flow Diagrams DFD Symbols – Process symbol • Receives input data and produces output that has a different content, form, or both • Contain the business logic, also called business rules • Referred to as a black box 8
- 9. Data Flow Diagrams DFD Symbols – Data flow symbol • Spontaneous generation • Black hole • Gray hole 9
- 10. Data Flow Diagrams DFD Symbols – Data store symbol 10
- 11. Data Flow Diagrams DFD Symbols – Entity Symbol • Terminators • Source • Sink 11
- 12. Creating a Set of DFDs Create a graphical model of the information system based on your fact-finding results Three-step process – Step 1: Draw a context diagram – Step 2: Draw a diagram 0 DFD – Step 3: Draw the lower-level diagrams 12
- 13. Creating a Set of DFDs 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 13
- 14. Creating a Set of DFDs Guidelines for Drawing DFDs – Do not cross lines – Provide a unique name and reference number for each process – Obtain as much user input and feedback as possible 14
- 15. Creating a Set of DFDs Step 1: Draw a Context Diagram – Context diagram – Process 0 15
- 16. Creating a Set of DFDs • Step 2: Draw a Diagram 0 DFD 16
- 17. Creating a Set of DFDs 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 17
- 18. Creating a Set of DFDs Step 3: Draw the LowerLevel Diagrams – Must use leveling and balancing techniques – Leveling examples • Exploding, partitioning, or decomposing 18
- 19. Creating a Set of DFDs Step 3: Draw the Lower-Level Diagrams – Balancing • Ensures that the input and output data flows of the parent DFD are maintained on the child DFD 19
- 20. Data Dictionary A data dictionary, or data repository, is a central storehouse of information about the system’s data An analyst uses the data dictionary to collect, document, and organize specific facts about the system Also defines and describes all data elements and meaningful combinations of data elements 20
- 21. Data Dictionary A data element, also called a data item or field, is the smallest piece of data that has meaning Data elements are combined into records, also called data structures A record is a meaningful combination of related data elements that is included in a data flow or retained in a data store 21
- 22. Data Dictionary Documenting the Data Elements – You must document every data element in the data dictionary – The objective is the same: to provide clear, comprehensive information about the data and processes that make up the system 22
- 23. Data Dictionary Documenting the Data Elements – The following attributes usually are recorded and described • • • • • Data element name and label Alias Type and length Default value Acceptable values - Domain and validity rules 23
- 24. Data Dictionary Documenting the Data Elements – The following attributes usually are recorded and described • • • • Source Security Responsible user(s) Description and comments 24
- 25. Data Dictionary Documenting the Data Flows – The typical attributes are as follows • • • • • • • Data flow name or label Description Alternate name(s) Origin Destination Record Volume and frequency 25
- 26. Data Dictionary Documenting the Data Stores – Typical characteristics of a data store are • • • • • Data store name or label Description Alternate name(s) Attributes Volume and frequency 26
- 27. Data Dictionary Documenting the Processes – Typical characteristics of a process • • • • Process name or label Description Process number Process description 27
- 28. Data Dictionary Documenting the Entities – Typical characteristics of an entity include • • • • • Entity name Description Alternate name(s) Input data flows Output data flows 28
- 29. Data Dictionary Documenting the Records – Typical characteristics of a record include • • • • Record or data structure name Definition or description Alternate name(s) Attributes 29
- 30. Data Dictionary Data Dictionary Reports – Many valuable reports • An alphabetized list of all data elements by name • A report describing each data element and indicating the user or department that is responsible for data entry, updating, or deletion • A report of all data flows and data stores that use a particular data element 30
- 31. Process Description Tools • A process description documents the details of a functional primitive, which represents a specific set of processing steps and business logic 31
- 32. Process Description Tools Modular Design – Based on combinations of three logical structures, sometimes called control structures which serve as building blocks for the process 1.Sequence 2.Selection 3.Iteration - looping 32
- 33. Process Description Tools Structured English – Must conform to the following rules • Use only the three building blocks of sequence, selection, and iteration • Use indentation for readability • Use a limited vocabulary, including standard terms used in the data dictionary and specific words that describe the processing rules 33
- 34. Process Description Tools Structured English – Might look familiar to programming students because it resembles pseudocode 34
- 35. Process Description Tools Decision Tables 35
- 36. Process Description Tools • Decision Tables 36
- 37. Process Description Tools Decision Trees 37
- 38. Logical Versus Physical Models 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 38
- 39. Logical Versus Physical Models Sequence of Models – Many 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 that extra step allows them to understand the current system better 39
- 40. Logical Versus Physical Models 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, and a physical model of the new system – The only disadvantage of the four-model approach is the added time and cost 40
- 41. Chapter Summary 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 41
- 42. Chapter Summary 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 42
- 43. Chapter Summary The data dictionary is the central documentation tool for structured analysis 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 43
- 44. Chapter Summary • Chapter 4 Complete 44