1. Database Development Lifecycle
Database Design
Database Development Lifecycle

2. Why Database? From Data …
Simple dumping of data on the storage medium provides little value.
CUSTOMER
id name address country pay due
100 J. Rodney 12 High Rd., Leeds UK 33.75
523 E. Hoover 52 Ln. Muncie, IN USA 0
800 M. Old Box. 9, Miami, FL USA 12.50
PRODUCT
product_id title cost sale price
Joy of Living
Learning Judo
Your Dream Home
SALE
id zone product_id quantity total price
100 UK
523 USMW
100 UK
800 USSE
Database System

3. Why Database? … Towards Information
The goal is not just storage of data, but ultimately the extraction of information to support decision making by key people and groups in the organization.
Data  Information (e.g. reports, tabulations, graphs)  Decisions *
- Summarized fact or information -
* In the UK ZONE, Joy of Living had a sale of $38.50, and Learning Judo had a sale of $25.
** UK ZONE had the total sale of $63.50, USMW had $24.25, and USSE had $19.25.
SALE by Zone**
Title UK USMW USSE total
Joy of Living
Learning Judo
Your Dream Home
Database System

4. Why Database? … For Decision Making
(DBMS)
Database Systems: Design, Implementation, & Management: Rob & Coronel
Database System

5. Database Design: Intro
Database System
Provides data collection 수집, storage 저장, and retrieval 검색
Composed of people, hardware, software, database(s), procedures, and application programs
Database Design
Foundation of a successful database system 휼륭한 DB system의 기반
Should promote
Data integrity 데이터 무결성
Prevent data redundancies 반복 & anomalies 오류
Must yield a database that
is efficient in its provision of data access 효율적인 데이터 접근
meet the objectives of the database system and serves the needs of its users DB시스템의 목적과 이용자의 요구 만족
Database Design

6. Data Redundancy (데이터의 반복성)
Database Systems: Design, Implementation, & Management: Rob & Coronel
Database Design

7. Database Systems: Design, Implementation, & Management: Rob & Coronel
Data Anomaly 데이터의 오류
Update anomalies 수정오류
- Data inconsistencies resulting from “islands of information” problem
Insertion Anomalies 삽입오류
- Creation of bogus record when adding new data (e.g. new agent)
Deletion Anomalies 삭제오류
- Unintended deletion of related data (e.g. agent data when deleting customer)
Database Systems: Design, Implementation, & Management: Rob & Coronel
Database System

8. Database Development Database Construction DB 구축
System Construction 시스템 구축
System Analysis 시스템 분석
Establish the need and extent of an information system
System Development 시스템 개발
Design & implement the information system
Database Construction DB 구축
Planning & Analysis 기획분석
Analyze data environment & Define database objectives
Database Development
Design 설계
Construct a data model & establish data management processes
Implementation 구현
Create the storage structure (e.g., tables) & user interface for data management
Maintenance 유지보수
(corrective & adaptive) modification, backup & recovery
Database Design

9. Database Development Lifecycle
Planning & Analysis
기획분석
Design
개념 설계
Implementation 구현
Maintenance 정비
 Database Objectives
Business Rules
Data Model
Modification
Backup & Recovery
Security
DBMS Tables
User Interface
SQL Queries
Database Design

10. Database Lifecycle: Planning & Analysis
Database Design
Implement
Maintain
Define Database Objectives DB목적 설정
What will the database (DB) do?
What tasks 업무/작업 will the DB support?
Data Entry, Update, Search
What information will the DB provide?
Q & A
Study the DB environment
How does the business operate?
Who are the players?
How does the information flow?
Examine the data
Sample Q&A: Recipe Database
Query
Result
recipe name
recipe info
(ingredients, steps, …)
ingredients
recipe names
 recipe info
main ingredient
(meat, fish, …)
recipe type
(diet, diabetic, …)
recipe category
(soup, desert, …)
budget, time
Database Design

11. Database Lifecycle: Database Design
Planning & Analysis
Database Design
Implement
Maintain
Create a Database Model DB 모델 제작
that can achieve the database objectives
Conceptual Design – ER Modeling
Logical Design – Relational Schema & Normalization
Physical Design – Schema into DBMS (Table Creation)
What is a Database Model?
Abstract data structure of the real-world items
실제 항목의 추상적인 data 구조
Need to understand how business works & what role data plays
E-R model verification
E-R model is verified against proposed system processes.
End-user views and required transactions
Access paths, security, concurrency control
Business-imposed data requirements and constraints
Database Design

12. Database Design: Conceptual Design
Planning & Analysis
Database Design
Implement
Maintain
Conceptual Design Steps
Enumerate the Business Rules
How does the business work?
Construct the Data Model
Identify Entities, Relationship, Attributes & draw an ER Diagram
Verify the Data Model
Does the data model support the fulfillment of database objectives?
E-R model verification
E-R model is verified against proposed system processes.
End-user views and required transactions
Access paths, security, concurrency control
Business-imposed data requirements and constraints
Database Design

13. Conceptual Design: Business Rules
Planning & Analysis
Database Design
Implement
Maintain
What 조직 내 정확한 업무 기술
Brief, precise, and unambiguous descriptions of operations in an organization
Based on policies, procedures, or principles within a specific organization
Why 정확한 data model 설계를 위하여
Promote creation of an accurate data model
Enhance understanding & facilitate communication
How (sources)
Interviews, Documentation, Observation
Examples
A painter can draw many paintings. A painting is drawn by a single painter.
A teacher can teach 0 to 6 courses per semester.
A course is taught by a single teacher.
A student must take at least 1 and at most 6 courses.
A course can have 10 to 40 students. 1 M
PAINTER
draws
PAINTING 1 M
TEACHER
teaches
COURSE N
takes M
STUDENT
Database Design

14. Conceptual Design: Data Modeling
Planning & Analysis
Database Design
Implement
Maintain
What is Data Modeling?
A model is a representation of reality that retains only carefully selected essential details.
Logical organization of data for optimum information extraction and data manipulation
Why Model? 주요한 data 요소들을 이해하고 인식하기 위하여
To understand and identify essential data elements
How?
Identify Entities 개체, Attributes 속성, & Relationships 관계 ID
STUDENT
GPA
Major
Name
TEACHER
Office
Database Design

15. Database Design: Relational Schema
Planning & Analysis
Database Design
Implement
Maintain
Specification of the overall structure/organization of a database
Relations
Entities w/ Attributes
Primary key
Unique identifier
Foreign key
PK of related table
Relationship type (connectivity)
1:M, M:N, 1:1
Database Design

16. Database Design: Data Dictionary
Planning & Analysis
Database Design
Implement
Maintain
Detailed description of a data model
Lists attribute names and characteristics for each table in the database
Blueprint & documentation of a database
Database Systems: Design, Implementation, & Management: Rob & Coronel
Database Design

17. Database Design: Lifecycle
Define Database Objectives DB 목적 설정
What information will the database provide?
Examine the Data Environment data 환경 조사
How does the business work & what data are used?
Construct the Data Model data모델 구축
Enumerate the Business Rule.
Identify Entities & Relationships between them.
Define Attributes (and primary & foreign keys) for each entity
Create an initial E-R diagram
Normalize the entities 개체 정규화
Process for evaluating & designing good table structures
Verify the Data Model data모델 확인
Does the data model support the database objectives?
If not, modify the Data Model
Database Design

18. Data Model: University Example
Database Design

19. Appendix
Database System

20. DB Design - Conceptual Design: Data Analysis & Requirements
Planning & Analysis
Database Design
Implement
Maintain
DB Design - Conceptual Design: Data Analysis & Requirements
Discover the data that can be transformed into desired information
Information Need
What kind of information is needed?
what output (queries & reports) must be generated by the system?
User Characteristics
Who will use the information?
How will information be used?
Information Source
Where is the information to be found?
How is the information to be extracted?
Information Constitution
What data elements are needed to produce the information?
What are the data attributes and relationships?
What data transformations are to be used to produce the information?
Develop a thorough understanding of the company’s data
Flow, uses, characteristics
Data Flow Diagram
Data sources
Interviews, direct observation
Business Rules
Narrative description of policy & procedures
Database System

21. Conceptual Design – ER Modeling: Business Rules
Planning & Analysis
Database Design
Implement
Maintain
Conceptual Design – ER Modeling: Business Rules
What: Brief, precise, and unambiguous descriptions of operations in an organization
based on policies, procedures, or principles within a specific organization
help to create and enforce actions within that organization’s environment
apply to any organization that stores and uses data to generate information
Why: Enhance understanding & facilitate communication
Standardize company’s view of data
Constitute a communications tool between users and designers
Allow designer to understand business process as well as the nature, role, and scope of data
Promote creation of an accurate data model
How (sources)
Interviews
Company managers, Policy makers, Department managers, End users
Written documentation
Procedures, Standards, Operations manuals
Observation
Business operations
Examples
A painter can draw many paintings. A painting is drawn by a single painter.
A teacher can teach 0 to 6 courses per semester. A student must take at least 1 and at most 6 courses.
Database System

22. Database Systems: Design, Implementation, & Management: Rob & Coronel
Planning & Analysis
Database Design
Implement
Maintain
Conceptual Design – ER Modeling: E-R Model Verification
E-R model is verified against proposed system processes.
Corroboration that intended processes can be supported by the database model
Careful reevaluation of the entities and detailed examination of attributes
Verification of business transactions as well as system and user requirements
May reveal additional entity and attribute details.
Verification process is iterative.
identify ER model’s central entity
identify modules/subsystems & components
identify transaction requirements
update/insert/delete/query/report
user interface
verify all processes against ER model
make necessary changes
repeat steps 2 through 5
E-R model is verified against proposed system processes.
End-user views and required transactions
Access paths, security, concurrency control
Business-imposed data requirements and constraints
Database Systems: Design, Implementation, & Management: Rob & Coronel
Database System

23. DB Design - Conceptual Design: DBMS Selection
Planning & Analysis
Database Design
Implement
Maintain
DB Design - Conceptual Design: DBMS Selection
What are the advantages & disadvantages?
Cost
purchase, maintenance, operational, training, etc.
Features & Tools
ease-of-use, performance, DB administration, etc.
application development tools
DB model
hierarchical, RDB, Object-oriented, etc.
Portability
platform, O/S, SQL
Hardware requirement
processor, RAM
Database System

24. DB Design: Logical & Physical Design
Planning & Analysis
Database Design
Implement
Maintain
DB Design: Logical & Physical Design
Logical Design
Translate conceptual design into internal model that maps objects in model to specific DBMS constructs
From software independent to software dependent
Detailed & functional descriptions of system components
Specify system processes and I/O.
e.g., table design, attribute definitions, access restrictions
Physical Design
Select the data storage and data access characteristics of the database
More important in older hierarchical and network models
Becomes more complex when data are distributed at different locations
Can affect the database performance
e.g. storage media, buffer size, etc.
Designers favor software that hides physical details
Database System

25. DB Lifecycle - Analysis: Feasibility Analysis
Planning & Analysis
Database Design
Implement
Maintain
DB Lifecycle - Analysis: Feasibility Analysis
Technological Feasibility
What hardware, software, and additional resources would be needed?
What is available in-house? What has to be purchased?
How will the new system be integrated?
Operational Feasibility
Who will design the system?
Who will maintain the system?
Who will do training or help-desk support?
Can the available personnel provide the time? New personnel necessary?
Economic Feasibility
Expected cost of the overall project ($)?
Software, hardware, application development, staff-time
Hidden cost (unforeseen)
Other costs
What is the competition/comparable unit doing?
Would data sharing among departments lead to additional expenses?
Benefits
How soon expected?
Database System

26. DB Lifecycle - Design: Data Modeling
Planning & Analysis
Database Design
Implement
Maintain
DB Lifecycle - Design: Data Modeling
What is Data Modeling?
A model is a representation of reality that retains only carefully selected essential details.
Logical organization of data for optimum information extraction and data manipulation
Why Model?
To understand and identify essential data elements
To produce a representation that can be transformed into a schema
How?
Data modeling involves
identifying entities, attributes, and relationships
Database System

27. Exercises

28. ERD Tips one AAA does many BBB one BBB is done by many AAA
a CCC has several BBB
each BBB belongs to one CCC
a, an, each  one  1
some, several  many  M 1 M
CCC
has
BBB N
does
a DDD owns one AAA
each AAA is owned by one DDD M 1 1
DDD
owns
AAA

29. ERD example A professor teaches many students.
A student is taught by several professors. M N
PROFESSOR
teaches
STUDENT
A professor teaches many classes.
A class is taught by a single professor. 1 M N M
PROFESSOR
teaches
CLASS
enrolls
STUDENT
A students enrolls in many classes.
A class has many students. M N
STUDENT
enrolls
CLASS

30. ERD example Chen ERD Crow’s Foot ERD M N PROFESSOR STUDENT 1 M M N
teaches
STUDENT
Chen ERD 1 M M N
PROFESSOR
teaches
CLASS
has
STUDENT
Crow’s Foot ERD
PROFESSOR
teaches
CLASS
has
STUDENT

31. ERD Example Business Rules
A professor can teach many classes. A class is taught by one professor.
A student can take many classes. A class can have many students.
A course can generate many classes. A class is generated by one course. 1 M M N
PROFESSOR
teaches
CLASS
has
STUDENT M
generates 1
COURSE

32. Data Modeling Exercises
Draw an E-R Diagram of the data model described by the business rules below.
One region can be the location for many stores. Each store is located in only one region.
Each store employs one or more employees. Each employee is employed by one store.
A job can be assigned to many employees. -- e.g., The "Sales Representative" job can be assigned to more than one employee at a time.
Each employee can have only one job assignment.
Draw an E-R Diagram of the data model described by the business rules below.
One region can be the location for many stores. Each store is located in only one region.
Each store employs one or more employees. Each employee is employed by one store.
A job can be assigned to many employees. -- e.g., The "Sales Representative" job can be assigned to more than one employee at a time.
Each employee can have only one job assignment.
Draw an E-R Diagram of the data model described by the business rules below.
One region can be the location for many stores. Each store is located in only one region.
Each store employs one or more employees. Each employee is employed by one store.
A job can be assigned to many employees. -- e.g., The "Sales Representative" job can be assigned to more than one employee at a time.
Each employee can have only one job assignment.
REGION
JOB 1 1
is location for
is assigned to M M 1 M
STORE
employees
EMPLOYEE
Database Design

33. Data Modeling Exercises
Identify the business rules and draw an E-R diagram of the situation described below.
For each professor, there may be multiple advisees. A professor teaches many classes and a class is taught by one professor.
Business Rules
A professor can advise many students.
A student is advised by one professor.
A professor can teach many classes.
A class is taught by one professor 1 M
PROFESSOR
teaches
CLASS 1
advises M
STUDENT
Database Design

34. Data Modeling Exercises
Sample DB
Create a data model (i.e. ERD) for the school database described below.
DB will keep track of advising and class information. DB should provide following information.
- The list of students advised for a given year & dates of advising sessions for each students
- Course listing for each year & student grades for each class
Create a data model (i.e. ERD) for the school database described below.
DB will keep track of advising and class information. DB should provide following information.
- The list of students advised for a given year & dates of advising sessions for each students
- Course listing for each year & student grades for each class
Create a data model (i.e. ERD) for the school database described below.
DB will keep track of advising and class information. DB should provide following information.
- The list of students advised for a given year & dates of advising sessions for each students
- Course listing for each year & student grades for each class
Create a data model (i.e. ERD) for the school database described below.
DB will keep track of advising and class information. DB should provide following information.
- The list of students advised for a given year & dates of advising sessions for each students
- Course listing for each year & student grades for each class
Business Rules
A professor can advise many students. A student is advised by one professor.
A professor can teach many classes. A class is taught by one professor.
A student can take many classes. A class can have many students.
A course can generate many classes. A class is generated by one course.
A professor can meet many times with an advisee. A student can meet many times with the advisor. 1 M
PROFESSOR
teaches
CLASS 1 1 N M 1 M
ADVISING
advises
generates
takes
ENROLL M M M M 1 M 1 1
STUDENT
COURSE
Database Design