The Database Environment and Development Process

Objectives

• Define terms
• Name limitations of conventional file processing
• Explain advantages of databases
• Identify costs and risks of databases
• List components of database environment
• Identify categories of database applications
• Describe database system development life cycle
• Explain prototyping and agile development approaches
• Explain roles of individuals
• Explain the three-schema architecture for databases

 

 

Definitions

• Database: organized collection of logically related data
• Data: stored representations of meaningful objects and events
• Structured: numbers, text, dates
• Unstructured: images, video, documents
• Information: data processed to increase knowledge in the person using the data
• Metadata: data that describes the properties and context of user data

 

 

 

Disadvantages of File Processing

• Program-Data Dependence
• All programs maintain metadata for each file they use
• Duplication of Data
• Different systems/programs have separate copies of the same data
• Limited Data Sharing
• No centralized control of data
• Lengthy Development Times
• Programmers must design their own file formats
• Excessive Program Maintenance
• 80% of information systems budget

 

 

 

Problems with Data Dependency

• 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 must have its own processing routines for reading, inserting, updating, and deleting data
• Lack of coordination and central control
• Non-standard file formats

 

 

 

Problems with Data Redundancy

• Waste of space to have duplicate data
• Causes more maintenance headaches
• The biggest problem:
• Data changes in one file could cause inconsistencies
• Compromises in data integrity

 

 

 

SOLUTION: The DATABASE Approach

• Central repository of shared data
• Data is managed by a controlling agent
• Stored in a standardized, convenient form

 

 

 

Advantages of the Database Approach

• Program-data independence
• Planned data redundancy
• Improved data consistency
• Improved data sharing
• Increased application development productivity
• Enforcement of standards
• Improved data quality
• Improved data accessibility and responsiveness
• Reduced program maintenance
• Improved decision support

 

 

 

Costs and Risks of the Database Approach

• New, specialized personnel
• Installation and management cost and complexity
• Conversion costs
• Need for explicit backup and recovery
• Organizational conflict

 

 

 

Elements of the Database Approach

• Data models
• Graphical system capturing nature and relationship of data
• Enterprise Data Model–high-level entities and relationships for the organization
• Project Data Model–more detailed view, matching data structure in database or data warehouse
• Entities
• Noun form describing a person, place, object, event, or concept
• Composed of attributes
• Relationships
• Between entities
• Usually one-to-many (1:M) or many-to-many (M:N)
• Relational Databases
• Database technology involving tables (relations) representing entities and primary/foreign keys representing relationships

 

 

 

Components of the Database Environment

• CASE Tools–computer-aided software engineering
• Repository–centralized storehouse of metadata
• Database Management System (DBMS) –software for managing the database
• Database–storehouse of the data
• Application Programs–software using the data
• User Interface–text and graphical displays to users
• Data/Database Administrators–personnel responsible for maintaining the database
• System Developers–personnel responsible for designing databases and software
• End Users–people who use the applications and databases

 

 

 

The Range of Database Applications

• Personal databases
• Two-tier Client/Server databases
• Multitier Client/Server databases
• Enterprise applications
• Enterprise resource planning (ERP) systems
• Data warehousing implementations

 

 

 

Enterprise Database Applications

• Enterprise Resource Planning (ERP)
• Integrate all enterprise functions (manufacturing, finance, sales, marketing, inventory, accounting, human resources)
• Data Warehouse
• Integrated decision support system derived from various operational databases

 

 

 

Enterprise Data Model

• First step in database development
• Specifies scope and general content
• Overall picture of organizational data at high level of abstraction
• Entity-relationship diagram
• Descriptions of entity types
• Relationships between entities
• Business rules

 

 

 

Two Approaches to Database and IS Development

• SDLC
• System Development Life Cycle
• Detailed, well-planned development process
• Time-consuming, but comprehensive
• Long development cycle
• Prototyping
• Rapid application development (RAD)
• Cursory attempt at conceptual data modeling
• Define database during development of initial prototype
• Repeat implementation and maintenance activities with new prototype versions

 

 

 

Database Schema

• External Schema
• User Views
• Subsets of Conceptual Schema
• Can be determined from business-function/data entity matrices
• DBA determines schema for different users
• Conceptual Schema
• E-R models
• Internal Schema
• Logical structures
• Physical structures
     

 

 

 

Managing Projects

• Project–a planned undertaking of related activities to reach an objective that has a beginning and an end
• Involves use of review points for:
• Validation of satisfactory progress
• Step back from detail to overall view
• Renew commitment of stakeholders
• Incremental commitment–review of systems development project after each development phase with rejustification after each phase

 

 

 

Managing Projects: People Involved

• Business analysts
• Systems analysts
• Database analysts and data modelers
• Users
• Programmers
• Database architects
• Data administrators
• Project managers
• Other technical experts