© Prentice Hall 1 Chapter 1: The Database Environment

Chapter 1 & 2 © Prentice Hall 2 Objectives Definition of terms Definition of terms Explain growth and importance of databases Explain growth and importance of databases Name limitations of conventional file processing Name limitations of conventional file processing Identify five categories of databases Identify five categories of databases Explain advantages of databases Explain advantages of databases Identify costs and risks of databases Identify costs and risks of databases List components of database environment List components of database environment Describe evolution of database systems Describe evolution of database systems

Chapter 1 & 2 © Prentice Hall 3 Definitions Data: stored representations of meaningful objects and events Data: stored representations of meaningful objects and events Structured: numbers, text, dates Structured: numbers, text, dates Unstructured: images, video, documents Unstructured: images, video, documents Database: organized collection of logically related data Database: organized collection of logically related data Information: data processed to increase knowledge in the person using the data Information: data processed to increase knowledge in the person using the data Metadata: data that describes the properties and context of user data Metadata: data that describes the properties and context of user data

Chapter 1 & 2 © Prentice Hall 4 Systems and Procedures Product flow and information flow Product flow and information flow Product flow: the flow of raw materials into assemblies and finally into finished goods. Product flow: the flow of raw materials into assemblies and finally into finished goods. Information flow: the creation of movement of the administrative and operational documentation necessary for product flow. Information flow: the creation of movement of the administrative and operational documentation necessary for product flow.

Chapter 1 & 2 © Prentice Hall 5 Product flow and Information flow CustomersEmployees Collection (8) Sales (5) Production (4) Distribution (6) Inventory (3) Receiving (2) Paying (9) Purchasing (1) Vendors Billing (7) Data to Information flow is as if raw material to production flow.

Chapter 1 & 2 © Prentice Hall 6 The evolution of product flow and information flow data processing information raw materials production finished goods InputOutput further processing ? technical support ?

Chapter 1 & 2 © Prentice Hall 7 Figure 1-1a Data in context Context helps users understand data

Chapter 1 & 2 © Prentice Hall 8 Graphical displays turn data into useful information that managers can use for decision making and interpretation Figure 1-1b Summarized data

Chapter 1 & 2 © Prentice Hall 9 Descriptions of the properties or characteristics of the data, including data types, field sizes, allowable values, and data context

Chapter 1 & 2 © Prentice Hall 10 Disadvantages of File Processing Program-Data Dependence Program-Data Dependence All programs maintain metadata for each file they use All programs maintain metadata for each file they use Duplication of Data Duplication of Data Different systems/programs have separate copies of the same data Different systems/programs have separate copies of the same data Limited Data Sharing Limited Data Sharing No centralized control of data No centralized control of data Lengthy Development Times Lengthy Development Times Programmers must design their own file formats Programmers must design their own file formats Excessive Program Maintenance Excessive Program Maintenance 80% of information systems budget 80% of information systems budget

Chapter 1 & 2 © Prentice Hall 11 Figure 1-3 Old file processing systems at Pine Valley Furniture Company Duplicate Data

Chapter 1 & 2 © Prentice Hall 12 Problems with Program Data Dependency Each application programmer must maintain his/her own data Each application programmer must maintain his/her own data Each application program needs to include code for the metadata of each file Each application program needs to include code for the metadata of each file Each application program must have its own processing routines for database operations: reading, inserting, updating, and deleting data Each application program must have its own processing routines for database operations: reading, inserting, updating, and deleting data Lack of coordination and central control Lack of coordination and central control Non-standard file formats Non-standard file formats

Chapter 1 & 2 © Prentice Hall 13 Problems with Data Redundancy Waste of space to have duplicate data Waste of space to have duplicate data Causes more maintenance headaches Causes more maintenance headaches The biggest problem: The biggest problem: Data changes in one file could cause inconsistencies Data changes in one file could cause inconsistencies Compromises in data integrity Compromises in data integrity

Chapter 1 & 2 © Prentice Hall 14 SOLUTION: The DATABASE Approach Central repository of shared data Central repository of shared data Data is managed by a controlling agent Data is managed by a controlling agent Stored in a standardized, convenient form Stored in a standardized, convenient form Requires a Database Management System (DBMS)

Chapter 1 & 2 © Prentice Hall 15 Database Management System DBMS manages data resources like an operating system manages hardware resources A software system that is used to create, maintain, and provide controlled access to user databases Order Filing System Invoicing System Payroll System DBMS Central database Contains employee, order, inventory, pricing, and customer data

Chapter 1 & 2 © Prentice Hall 16 Advantages of the Database Approach Program-data independence (PI) Program-data independence (PI) Planned (minimal) data redundancy (DR) Planned (minimal) data redundancy (DR) Improved data consistency Improved data consistency Improved data sharing Improved data sharing Increased application development productivity Increased application development productivity Enforcement of standards Enforcement of standards Improved data quality Improved data quality Improved data accessibility and responsiveness Improved data accessibility and responsiveness Reduced program maintenance Reduced program maintenance Improved decision support Improved decision support

Chapter 1 & 2 © Prentice Hall 17 Costs and Risks of the Database Approach New, specialized personnel New, specialized personnel Installation and management cost and complexity Installation and management cost and complexity Conversion costs Conversion costs Need for explicit backup and recovery Need for explicit backup and recovery Organizational conflict Organizational conflict

Chapter 1 & 2 © Prentice Hall 18 Figure 2-9 Three-tiered client/server database architecture Data tier Presentation tier Business logic tier

Chapter 1 & 2 © Prentice Hall 19 Evolution of DB Systems

© Prentice Hall 20 Chapter 2: The Database Development Process

Chapter 1 & 2 © Prentice Hall 21 Objectives Definition of terms Definition of terms Describe system development life cycle Describe system development life cycle Explain prototyping approach Explain prototyping approach Explain roles of individuals Explain roles of individuals Explain three-schema approach Explain three-schema approach Explain role of packaged data models Explain role of packaged data models Explain three-tiered architectures Explain three-tiered architectures Explain scope of database design projects Explain scope of database design projects Draw simple data models Draw simple data models

Chapter 1 & 2 © Prentice Hall 22 Information Systems Architecture (ISA) Conceptual blueprint for organization’s desired information systems structure Conceptual blueprint for organization’s desired information systems structure Consists of (6Ws): Consists of (6Ws): Processes – data flow diagrams, process decomposition, etc. (DFD- Data Flow Diagram) Processes – data flow diagrams, process decomposition, etc. (DFD- Data Flow Diagram) Data (e.g. Enterprise Data Model – ER Diagram) Data (e.g. Enterprise Data Model – ER Diagram) Data Network – topology diagram (like Fig 1-9) Data Network – topology diagram (like Fig 1-9) People – people management using project management tools (Gantt charts, etc.) People – people management using project management tools (Gantt charts, etc.) Events and points in time (when processes are performed. Use case diagram) Events and points in time (when processes are performed. Use case diagram) Reasons for events and rules (e.g., decision tables) Reasons for events and rules (e.g., decision tables) What How Where Who When Why

Chapter 1 & 2 © Prentice Hall 23 Data Flow Diagrams Data flow diagrams (DFDs) are graphical aids that describe an information system Data flow diagrams (DFDs) are graphical aids that describe an information system Advantages: Advantages: freedom from committing to the technical implementation of the system too early. freedom from committing to the technical implementation of the system too early. Further understanding the interrelatedness of systems and subsystems. Further understanding the interrelatedness of systems and subsystems. communicating current system knowledge to users. communicating current system knowledge to users.

Chapter 1 & 2 © Prentice Hall 24 Data Flow Diagrams Data flow diagram symbols Data flow diagram symbols Four basic symbols Four basic symbols Process Process Data flow Data flow Data store Data store External entity External entity

Chapter 1 & 2 © Prentice Hall 25 Process Data flows External entities

Chapter 1 & 2 © Prentice Hall 26 Data store

Chapter 1 & 2 © Prentice Hall 27

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Chapter 1 & 2 © Prentice Hall 29 Figure 2-2 Example of process decomposition of an order fulfillment function (Pine Valley Furniture) Decomposition = breaking large tasks into smaller tasks in a hierarchical structure chart Order form Credit status

Chapter 1 & 2 © Prentice Hall 30 Information Systems Architecture (ISA) Conceptual blueprint for organization’s desired information systems structure Conceptual blueprint for organization’s desired information systems structure Consists of (6Ws): Consists of (6Ws): Processes – data flow diagrams, process decomposition, etc. (DFD- Data Flow Diagram) Processes – data flow diagrams, process decomposition, etc. (DFD- Data Flow Diagram) Data (e.g. Enterprise Data Model – ER Diagram) Data (e.g. Enterprise Data Model – ER Diagram) Data Network – topology diagram (like Fig 1-9) Data Network – topology diagram (like Fig 1-9) People – people management using project management tools (Gantt charts, etc.) People – people management using project management tools (Gantt charts, etc.) Events and points in time (when processes are performed. Use case diagram) Events and points in time (when processes are performed. Use case diagram) Reasons for events and rules (e.g., decision tables) Reasons for events and rules (e.g., decision tables) What How Where Who When Why

Chapter 1 & 2 © Prentice Hall 31 Develop Enterprise Model Process: Data flow diagram (DFD) Process: Data flow diagram (DFD) Functional decomposition Iterative process breaking system description into finer and finer detail Data: Entity Relationship diagram (ER Diagram) Data: Entity Relationship diagram (ER Diagram) Planning matrixes Planning matrixes Describe interrelationships between planning objects

Chapter 1 & 2 © Prentice Hall 32 Data Dictionary Data Entity (table) Program Modules Data Entity (table) Data Element (field) Data Modeling using ERD

Chapter 1 & 2 © Prentice Hall 33 Example business function-to- data entity matrix (Fig. 2-3) Higher priority Spot missing entity

Chapter 1 & 2 © Prentice Hall 34 Planning Matrixes Describe relationships between planning objects in the organization Describe relationships between planning objects in the organization Types of matrixes: Types of matrixes: Function-to-data entity Function-to-data entity Location-to-function Location-to-function Unit-to-function Unit-to-function IS-to-data entity IS-to-data entity Supporting function-to-data entity Supporting function-to-data entity IS-to-business objective IS-to-business objective

Chapter 1 & 2 © Prentice Hall 35 Database Schema Conceptual Schema Conceptual Schema E-R models–covered in Chapters 3 and 4 E-R models–covered in Chapters 3 and 4 External Schema External Schema User Views: schema for different users User Views: schema for different users Subsets of Conceptual Schema Subsets of Conceptual Schema Can be determined from business-function/data entity matrices Can be determined from business-function/data entity matrices Physical Schema (Internal Schema) Physical Schema (Internal Schema) Physical structures–covered in Chapters 5 and 6 Physical structures–covered in Chapters 5 and 6

Chapter 1 & 2 © Prentice Hall 36 Different people have different views of the database…these are the external schema The internal schema is the underlying design and implementation Figure 2-7 Three-schema architecture

Chapter 1 & 2 © Prentice Hall 37 Figure 2-8 Developing the three-tiered architecture

Chapter 1 & 2 © Prentice Hall 38 Information Engineering Top-down planning–a generic IS planning methodology for obtaining a broad understanding of the IS needed by the entire organization Top-down planning–a generic IS planning methodology for obtaining a broad understanding of the IS needed by the entire organization Four steps to Top-Down planning: Four steps to Top-Down planning: Planning Planning Analysis Analysis Design Design Implementation Implementation

Chapter 1 & 2 © Prentice Hall 39 Two Approaches to Database and IS Development SDLC SDLC System Development Life Cycle System Development Life Cycle Detailed, well-planned development process Detailed, well-planned development process Time-consuming, but comprehensive Time-consuming, but comprehensive Long development cycle Long development cycle Prototyping Prototyping Rapid application development (RAD) Rapid application development (RAD) Cursory attempt at conceptual data modeling Cursory attempt at conceptual data modeling Define database during development of initial prototype Define database during development of initial prototype Repeat implementation and maintenance activities with new prototype versions Repeat implementation and maintenance activities with new prototype versions

Chapter 1 & 2 © Prentice Hall 40 Systems Development Life Cycle (see also Figures 2.4, 2.5) Planning Analysis Physical Design Implementation Maintenance Logical Design

Chapter 1 & 2 © Prentice Hall 41 à Systems planning à Purpose – identify problem’s nature/scope à Systems request – begins the process & describes desired changes/improvements à Systems planning – includes preliminary investigation or feasibility study à End product – preliminary investigation report Systems Development Life Cycle

Chapter 1 & 2 © Prentice Hall 42 à Systems analysis à Purpose is to learn exactly how the current system operates or determine what systems should do. à Fact-finding or requirements determination is used to define all functions of the current system Systems Development Life Cycle

Chapter 1 & 2 © Prentice Hall 43 à Options à Develop a system in-house à Purchase a commercial package à Modify an existing system à Stop development à The end product for this phase is the systems requirements document Systems Development Life Cycle

Chapter 1 & 2 © Prentice Hall 44 à Systems design à Purpose is to satisfy all documented requirements à identify what and how the system must do. à Identify all outputs, inputs, files, manual procedures, & application programs à user interface design, files organization and database design à Avoid misunderstanding through manager and user involvement à End product is system design specification Systems Development Life Cycle

Chapter 1 & 2 © Prentice Hall 45 à Systems implementation à Construct/deliver information system à Prepares functioning, documented system à Write, test, document application programs à User and manager approval obtained à File conversion occurs à Users, managers, IS staff trained to operate and support the system à Post-implementation evaluation performed Systems Development Life Cycle

Chapter 1 & 2 © Prentice Hall 46 Prototyping Database Methodology (Figure 2.6)

Chapter 1 & 2 © Prentice Hall 47 Prototyping Database Methodology (Figure 2.6) (cont.)

Chapter 1 & 2 © Prentice Hall 48 Prototyping Database Methodology (Figure 2.6) (cont.)

Chapter 1 & 2 © Prentice Hall 49 Prototyping Database Methodology (Figure 2.6) (cont.)

Chapter 1 & 2 © Prentice Hall 50 Prototyping Database Methodology (Figure 2.6) (cont.)

Chapter 1 & 2 © Prentice Hall 51 CASE Computer-Aided Software Engineering (CASE)–software tools providing automated support for systems development Computer-Aided Software Engineering (CASE)–software tools providing automated support for systems development Three database features: Three database features: Data modeling–drawing entity-relationship diagrams Data modeling–drawing entity-relationship diagrams Code generation–SQL code for table creation Code generation–SQL code for table creation Repositories–knowledge base of enterprise information Repositories–knowledge base of enterprise information

Chapter 1 & 2 © Prentice Hall 52 Managing Projects: People Involved Business analysts Business analysts Systems analysts Systems analysts Database analysts and data modelers Database analysts and data modelers Users Users Programmers Programmers Database architects Database architects Data administrators Data administrators Project managers Project managers Other technical experts Other technical experts

Chapter 1 & 2 © Prentice Hall 53 Figure 1-5 Components of the Database Environment