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Chapter 7

Data Design. Chapter 7. 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

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Chapter 7

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  1. Data Design Chapter 7

  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

  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 • 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 blueprintfor 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 formatto show a table’s structure, fields, and primary key Example: NAME (FIELD 1, FIELD 2, FIELD 3)

  26. Normalization • Repeating Groups and Unnormalized Designs • Repeating group • 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 transmissiontime, 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

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