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Chapter 9

Data Design. Chapter 9. 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 9

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  1. Data Design

    Chapter 9

  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 Terminology Definitions Entity: a person, place, thing, or event which data is collected and maintained Table or file: a set of related records, a table describes an entity Record AKA Tuple Field AKA attribute Common field: an attribute that appears in more than one entity. Used to link entities
  5. Data Design Terminology Key Fields (p. 399) 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
  6. Data Design Terminology Referential Integrity(參照完整性): Validity checks to 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: Ex. an order with no related customer in the customer table
  7. Example of Referential Integrity in Access
  8. 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
  9. 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 Consider the nature of relationships that link them
  10. Entity-Relationship Diagrams Types of Relationships: p. 402-404 One-to-one relationship (1:1) One-to-many relationship (1:M) Many-to-many relationship (M:N) Associative entity Cardinality Cardinality notation P.402-404, 405 Example of ERD P. 404
  11. 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
  12. 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)
  13. Normalization Repeating Groups and Unnormalized Designs Repeating group Often occur in manual documents prepared by users Unnormalized design Another example: see supplement file
  14. Unnormalized example ORDER (ORDER-NUM, ORDER-DATE, (PRODUCT-NUM, PRODUCT-DESC, NUM-ORDERED))
  15. 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. 408
  16. 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 that does not have a sale record is a problem Deleting a product is a problem: what if deleting product number 633? You lost all the info about this product
  17. 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
  18. 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. 410
  19. Normalization Third Normal Form A table design is in third normal form (3NF) if it is in 2NF and if NOnonkey 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. 411, Figure 9-25
  20. Normalization A Normalization Example (p. 413-417) To show the normalization process, consider the familiar situation, which depicts several entities in a school advising system: ADVISOR, COURSE, and STUDENT
  21. Unnormalized form STUDENT (STUDENT-NUMBER, STUDENT-NAME, TOTAL-CREDITS, GPA, ADVISOR-NUMBER, ADVISOR-NAME, (COURSE-NUMBER, COURSE-DESC, NUMBER-CREDIT, GRADE))
  22. 1NF STUDENT (STUDENT-NUMBER, STUDENT-NAME, TOTAL-CREDITS, GPA, ADVISOR-NUMBER, ADVISOR-NAME, COURSE-NUMBER, COURSE-DESC, NUMBER-CREDIT, GRADE)
  23. 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)
  24. 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)
  25. New ERD P. 417
  26. More example 3NF supplements
  27. 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 More example: Figure 9-39, pp. 421-422
  28. 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
  29. 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
  30. Example of file system
  31. Data Design Concepts Overview of File Processing Potential problems Data redundancy Data integrity Rigid data structure
  32. 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 Fig. 9-5 (p. 390) A typical database environment
  33. 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
  34. 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
  35. DBMS Components A DBMS provides an interface between a database and users who need to access the data
  36. DBMS Components Interfaces for Users, Database Administrators, and Related Systems Users Query language (p. 394 for example) Query by example (QBE) SQL (structured query language) Database Administrators (DBA) A DBA is responsible for DBMS management and support
  37. 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
  38. 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 Open Database Connectivity (ODBC) A protocol for different vendor software to interact and exchange data ODBC – open database connectivity JDBC – Java database connectivity
  39. 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
  40. 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 software that integrates different applications and allows them to exchange data P. 396 for figure 9-9
  41. 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
  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. 422, figure 9-41, 42
  43. 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
  44. 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. 419, Fig. 9-37) Cipher codes (用於code價錢） Action codes （A for add, D for delete)
  45. Data Storage and Access Data storage and access involve strategic business tools Data warehouse - dimensions
  46. 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
  47. 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
  48. Data Control User ID Password Permissions Encryption Backup Recovery procedures Audit log files Audit fields
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