Transcript Chapter 2 of Database Design, Application Development and

Chapter 2
Introduction to Database
Development
McGraw-Hill/Irwin
Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved.
Outline
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Context for database development
Goals of database development
Phases of database development
CASE tools
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Information System
INPUTS
Loan Applications
OUTPUTS
PROCESSES
ENVIRONM ENT
Pay ments
Student Loan
Processing
System
Delinquency
Notices
ENVIRONM ENT
Statements
Cash
Disbursements
Status
Changes
DATABASE
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Traditional Life Cycle
Preliminary
Investigation
Problem Statement,
Feasibility Study
Systems
Analysis
Feedback
Sy stem Requirements
Systems
Design
Design Specif ications
Systems
Feedback Implementation
Operational
Sy stem
Maintenance
Feedback
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Development Alternatives
 Difficulties
 Operational system is produced late
 Rush to begin implementation
 Requirements are difficult to capture
 Alternative methodologies
 Spiral approaches
 Rapid application development
 Prototypes may reduce risk
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Graphical Models
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Explicit or implicit
Data model
Process model
Environment interaction model
Emphasize data model
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Broad Goals of Database
Development
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Develop a common vocabulary
Define data meaning
Ensure data quality
Provide efficient implementation
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Develop a Common
Vocabulary
 Diverse groups of users
 Difficult to obtain acceptance of a common
vocabulary
 Compromise to find least objectionable
solution
 Unify organization by establishing a
common vocabulary
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Define Meaning of Data
 Business rules support organizational
policies
 Restrictiveness of business rules
 Too restrictive: reject valid business
interactions
 Too loose: allow erroneous business
interactions
 Exceptions allow flexibility
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Data Quality
 Poor data quality leads to poor decision
making
 Difficult customer communication
 Inventory shortages
 Cost-benefit tradeoff to achieve desired
level of data quality
 Long-term effects of poor data quality
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Data Quality Measures
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Completeness
Lack of ambiguity
Timeliness
Correctness
Consistency
Reliability
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Efficient Implementation
 Supersedes other goals
 Optimization problem
 Maximize performance
 Subject to constraints of data quality, data
meaning, and resource usage
 Difficult problem:
 Number of choices
 Relationships among choices
 DBMS specific
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Database Development Phases
Data
requirements
Conceptual Data
Modeling
ERD
Logical Database
Design
Tables
Distributed Database
Design
Distribution Schema
Physical Database
Design
Internal Schema,
Populated DB
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Conceptual Data Modeling
 Information content of the database
 Entity relationship diagram (ERD) showing
entity types and relationships
 Historically, DBMSs did not support many
constraints.
 Diverse formats for database requirements
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Logical Database Design
 Refine conceptual design
 Convert ERD to table design
 Analyze design for excessive
redundancies
 Normalization: tool to reason about
redundancies
 Add constraints to enforce business rules
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Distributed Database Design
 Location of data and processing
 Performance orientation, not information
content orientation
 Allocate subsets of database to different
sites
 Replicate subsets of database to improve
availability
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Physical Database Design
 Performed at each independent database
site
 Minimize response time without
consuming excessive resources
 Tradeoffs: retrieval versus update
 Flexible designs versus specialized
designs
 Decisions: indexes, data placement
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Splitting Conceptual Design
Conceptual Data Modeling
Data Requirements
View Design
View ERDs
View Integration
Entity Relationship Diagrams
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Cross Checking Requirements
System
Requirem ents
Data Requirements
Database
Deve lopm e nt
Application Requirements
Cross
Checking
ERDs, Table Design,
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Application
Deve lopm e nt
Process Models,
Interaction Models,
Prototy pes
Operational
Applications
Operational
Database
Ope rational
System
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Design Skills
 Soft
 Qualitative
 Degree of subjectivity
 People-oriented
 Hard
 Quantitative
 Objective
 Intensive data analysis
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Design Skills in Phases
Data Requirements
Design Skills
Conce ptual Data
M ode ling
Soft
Entity Relationship
Diagrams
Logical Databas e
Des ign
Relational Database
Tables
Dis tribute d
Databas e Des ign
Distribution Schema
Physical
Databas e Des ign
Internal Schema, Populated Database
Hard
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Features of CASE Tools
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Diagramming
Documentation
Analysis
Prototyping
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Classification of CASE Tools
 Front-end vs. Back-end
 Front-end emphasize data modeling and
logical analysis
 Back-end emphasize code generation and
physical design
 DBMS dependent vs. DBMS independent
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Commercial CASE Tools
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PowerDesigner 10
Oracle Designer 10g
Visual Studio .Net Enterprise Architect
ERWin Data Modeler
ER/Studio
Visible Analyst
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ER Assistant
 CASE tool distributed with the textbook
 Customized for this textbook: supports the
ERD notation used in Chapters 5 and 6
 Drawing tool
 Diagram checking
 Easy to use and powerful tool
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Visio Professional
 Entry level version of Visual Studio .Net
Enterprise Architect
 Drawing tools
 Stencils for database diagrams
 Glue feature to retain connections
 Data dictionary support
 Analysis tools
 Diagram layout
 Reverse engineering
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Summary
 Background for Chapters 5 to 8
 Relationship to information systems
development
 Broad goals
 Development phases
 CASE tool features
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Questions & Discussion
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