1. Chapter 7
Data Design

2. Introduction
You will develop a physical plan for data organization, storage, and retrieval
Begins with a review of data design concepts and terminology, then discusses file-based systems and database systems, including Web-based databases
Concludes with a discussion of data storage and access, including strategic tools such as data warehousing and data mining, physical design issues, logical and physical records, data storage formats, and data control 4

3. Data Design Concepts Data Structures
A file or table contains data about people, places, things, or events that interact with the system
File-oriented system
File processing system
Database system

4. Data Design Concepts Overview of File Processing
Uses various types of files
Master file
Table file
Transaction file
Work file – scratch file
Security file
History file

5. Example of file system

6. Data Design Concepts Overview of File Processing Potential problems
Data redundancy
Data integrity
Rigid data structure

7. Data Design Concepts Overview of Database Systems
A properly design database system offers a solution to the problems of file processing
Provides an overall framework that avoids data redundancy and supports a real-time, dynamic environment
Database management system (DBMS)
The main advantage of a DBMS is that it offers timely, interactive, and flexible data access

8. Data Design Concepts Overview of Database Systems Advantages
Scalability(擴充性)
Better support for client/server systems
Economy of scale
Flexible data sharing
Enterprise-wide application – database administrator (DBA)
Stronger standards
Controlled redundancy
Better security
Increased programmer productivity
Data independence

9. Data Design Concepts Database Tradeoffs
Because DBMSs are powerful, they require more expensive hardware, software, and data networks capable of supporting a multi-user environment
More complex than a file processing system
Procedures for security, backup, and recovery are more complicated and critical

10. DBMS Components
A DBMS provides an interface between a database and users who need to access the data

11. DBMS Components
Interfaces for Users, Database Administrators, and Related Systems
Users
Query language (p. 310 for example)
Query by example (QBE)
SQL (structured query language)
Database Administrators (DBA)
A DBA is responsible for DBMS management and support

12. DBMS Components Data Manipulation Language Schema (綱目)
A data manipulation language (DML) controls database operations, including storing, retrieving, updating, and deleting data
Schema (綱目)
The complete definition of a database, including descriptions of all fields, tables, and relationships, is called a schema
You also can define one or more subschemas

13. DBMS Components Physical Data Repository
The data dictionary is transformed into a physical data repository, which also contains the schema and subschemas
The physical repository might be centralized, or distributed at several locations, and different venders of databases might be used
Need ODBC-compliant software to resolve potential database connectivity and access problems
ODBC – open database connectivity
JDBC – Java database connectivity

14. Web-Based Database Design
Characteristics of Web-Based Design
In a Web-based design, the Internet serves as the front end, or interface, for the database management system
Internet technology provides enormous power and flexibility
Web-based systems are popular because they offer ease of access, cost-effectiveness, and worldwide connectivity

15. Web-Based Database Design
Connecting a Database to the Web
Database must be connected to the Internet or intranet
Database and internet speak two different “languages”
Middleware is needed
A softwaqre that integrates different applications and allows them to exchange data
P. 312 for figure 7-9

16. Web-Based Database Design
Data Security
Web-based data must be totally secure, yet easily accessible to authorized users
To achieve this goal, well-designed systems provide security at three levels: the database itself, the Web server, and the telecommunication links that connect the components of the system

17. Data Design Terminology
Definitions
Entity: a person, place, thing, or event which data is collected and maintained
Table or file: a set of related records
Record
AKA Tuple
Field
AKA attribute
Common field: an attribute that appears in more than one entity. Used to link entities

18. Data Design Terminology
Key Fields (p. 315)
Primary key: unique field
Combination key
Composite key
Concatenated key
Multi-valued key
Candidate key: could be a p.k.
Nonkey field: not a p.k.or candidate key
Foreign key: 別的table的primary key
Secondary key: not unique, zip code

19. Data Design Terminology
Referential Integrity: Validity checks can help avoid data input errors
A set of rules that avoids data inconsistency and quality problems
A foreign key value cannot be entered in one table unless it matches a existing primary key in another table
EX. Referential integrity would prevent you from entering a customer order in an order table unless that customer already exists in the customer table.
orphan

20. Example of Referential Integrity in Access

21. Entity-Relationship Diagrams
Provides an overall view of the system, and a blueprint for creating the physical data structures
An entity is a person, place, thing, or event for which data is collected and maintained

22. Entity-Relationship Diagrams
Drawing an ERD
The first step is to list the entities that you identified during the fact-finding process and to consider the nature of the relationships that link them

23. Entity-Relationship Diagrams
Types of Relationships: p. 318~320
One-to-one relationship (1:1)
One-to-many relationship (1:M)
Many-to-many relationship (M:N)
Associative entity
Cardinality
Cardinality notation
P.318, 321

24. Normalization Table design
Involves four stages: unnormalized design, first normal form, second normal form, and third normal form
Most business-related databases must be designed in third normal form

25. Normalization Standard Notation Format
Designing tables is easier if you use a standard notation format to show a table’s structure, fields, and primary key
Example: NAME (FIELD 1, FIELD 2, FIELD 3)

26. Normalization Repeating Groups and Unnormalized Designs
Often occur in manual documents prepared by users
Unnormalized design

27. Unnormalized example
ORDER (ORDER-NUM, ORDER-DATE, (PRODUCT-NUM, PRODUCT-DESC, NUM-ORDERED))

28. Normalization First Normal Form
A table is in first normal form (1NF) if it does not contain a repeating group
To convert, you must expand the table’s primary key to include the primary key of the repeating group
ORDER (ORDER-NUM, ORDER-DATE, PRODUCT-NUM, PRODUCT-DESC, NUM-ORDERED)
See p. 324

29. Normalization Problems found in First Normal Form
Four kinds of problems are found with 1NF designs
Consider the work necessary to change a particular product’s description
1NF tables can contain inconsistent data
Adding a new product is a problem
Deleting a product is a problem

30. Normalization Second Normal Form
A table is in the 2NF if it is in 1NF and if all fields that are NOT part of the primary key are functionally dependent on the entire primary key
To understand second normal form (2NF), you must understand the concept of functional dependence
Functionally dependent：函數相依
Field X is functionally dependent on field Y if the value of field X depends on the value of field Y
ORDER_DATE is FD on ORDER_NUM
DRODUCT_DESC is FD on PRODUCT_NUM

31. Normalization Second Normal Form
A standard process exists for converting a table from 1NF to 2NF
Create and name a separate table for each field in the existing primary key
Create a new table for each possible combination of the original primary key fields
Study the three tables and place each field with its appropriate primary key
Example: p. 326

32. Normalization Third Normal Form
A table design is in third normal form (3NF) if it is in 2NF and if NO nonkey field is dependent on another nonkey field
3NF design avoids redundancy and data integrity problems that still can exist in 2NF designs
To convert the table to 3NF, you must remove all fields from the 2NF table that depend on another nonkey field and place them in a new table that uses the nonkey field as a primary key
Example: p. 327, Figure 7-25

33. Normalization A Normalization Example (p. 329-333)
To show the normalization process, consider the familiar situation, which depicts several entities in a school advising system: ADVISOR, COURSE, and STUDENT

34. Unnormalized form
STUDENT (STUDENT-NUMBER, STUDENT-NAME, TOTAL-CREDITS, GPA, ADVISOR-NUMBER, ADVISOR-NAME, (COURSE-NUMBER, COURSE-DESC, NUMBER-CREDIT, GRADE))

35. 1NF
STUDENT (STUDENT-NUMBER, STUDENT-NAME, TOTAL-CREDITS, GPA, ADVISOR-NUMBER, ADVISOR-NAME, COURSE-NUMBER, COURSE-DESC, NUMBER-CREDIT, GRADE)

36. 2NF
STUDENT (STUDENT-NUMBER, STUDENT-NAME, TOTAL-CREDITS, GPA, ADVISOR-NUMBER, ADVISOR-NAME) not 3NF
COURSE (COURSE-NUMBER, COURSE-DESC, NUMBER-CREDIT)
GRADE (STUDENT-NUMBER, COURSE-NUMBER, GRADE)

37. 3NF
STUDENT (STUDENT-NUMBER, STUDENT-NAME, TOTAL-CREDITS, GPA, ADVISOR-NUMBER)
ADVISOR (ADVISOR-NUMBER, ADVISOR-NAME)
COURSE (COURSE-NUMBER, COURSE-DESC, NUMBER-CREDIT)
GRADE (STUDENT-NUMBER, COURSE-NUMBER, GRADE)

38. New ERD
P. 333

39. Steps in Database Design
Create the initial ERD
Assign all data elements to entities
Create 3NF designs for all tables, taking care to identify all primary, secondary, and foreign keys
Verify all data dictionary entries
After creating your final ERD and normalized table designs, you can transform them into a database

40. Using Codes During Data Design
Overview of Codes
Because codes often are used to represent data, you encounter them constantly in your everyday life
They save storage space and costs, reduce transmission time, and decrease data entry time
Can reduce data input errors

41. Using Codes During Data Design
Types of Codes
Sequence codes
Block sequence codes (e.g. 100 level course– entry level course)
Alphabetic codes
Category codes (CS, EE)
Abbreviation codes – mnemonic codes (NY, JFK)
Significant digit codes (e.g. zipcode)
Derivation codes (p. 335, Fig. 7-37)
Cipher codes (用於code價錢）
Action codes （A for add, D for delete)

42. Database Models Relational Databases
The relational model was introduced during the 1970s and became popular because it was flexible and powerful
Because all the tables are linked, a user can request data that meets specific conditions
New entities and attributes can be added at any time without restructuring the entire database
Example in p. 338, figure 7-41, 42

43. Data Storage and Access
Data storage and access involve strategic business tools
Data warehouse - dimensions

44. Data Storage and Access
Strategic tools for data storage and access
Data Mining: works best when you have clear, measurable goals
Walmart’s example of data mining

45. Data Control
File and database control must include all measures necessary to ensure that data storage is correct, complete, and secure
A well-designed DBMS must provide built-in control and security features, including subschemas, passwords, encryption, audit trail files, and backup and recovery procedures to maintain data

46. Data Control User ID Password Permissions Encryption Backup
Recovery procedures
Audit log files
Audit fields