Data Design and Organization: File Processing and Database Systems

1. CHAPTER 6DATA DESIGN

2. Chapter Objectives • Explain data design concepts and structures • Describe file processing systems • Explain database systems and define the components of a database management system (DBMS) • Describe Web-based data design

3. Chapter Objectives • Explain data design terminology, including entities, fields, common fields, records, files, tables, and key fields • Describe data relationships, draw an entity relationship diagram, define cardinality, and use cardinality notation • Explain the concept of normalization • Explain the importance of codes and describe various coding schemes

4. Chapter Objectives • Describe relational and object-oriented database models • Explain data warehousing and data mining • Differentiate between logical and physical storage and records • Explain data control measures

5. 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 controls

6. Data Design Concepts • Before constructing an information system, a systems analyst must understand basic design concepts, including data structures and the characteristics of file processing and database systems, including Web-based database design

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

8. Data Design Concepts • Overview of File Processing • Some companies still use file processing to handle large volumes of structured data on a regular basis • Although much less common today, file processing can be efficient and cost-effective in certain situations

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

10. Data Design Concepts • Overview of File Processing • Various types of files • Master file • Table file • Transaction file • Work file • Security file • History file

11. Data Design Concepts • The Evolution from File Systems to Database Systems • A properly designed 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

12. Data Design Concepts • The Evolution from File Systems to Database Systems • A database management system (DBMS) is a collection of tools, features, and interfaces that enables users to add, update, manage, access, and analyze the contents of a database • The main advantage of a DBMS is that it offers timely, interactive, and flexible data access

13. Data Design Concepts • The Evolution from File Systems to Database Systems • Advantages • Scalability • Better support for client/server systems • Economy of scale • Flexible data sharing • Enterprise-wide application – database administrator (DBA) • Stronger standards

14. Data Design Concepts • The Evolution from File Systems to Database Systems • Advantages • Controlled redundancy • Better security • Increased programmer productivity • Data independence

15. Data Design Concepts • The Evolution from File Systems to Database Systems • Although the trend is toward enterprise-wide database design, many companies still use a combination of centralized DBMSs and smaller, department-level database systems • The compromise, in many cases, is a client/server design, where processing is shared among several computers

16. DBMS Components • A DBMS provides an interface between a database and users who need to access the data • In addition to interfaces for users, database administrators, and related systems, a DBMS also has a data manipulation language, a schema and subschemas, and a physical data repository

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

18. DBMS Components • Interfaces for Users, Database Administrators, and Related Systems • Related information systems • A DBMS can support several related information systems that provide input to, and require specific data from, the DBMS • No human intervention is required for two-way communication

19. DBMS Components • Data Manipulation Language • A data manipulation language (DML) controls database operations, including storing, retrieving, updating, and deleting data • Some database products also provide an easy-to-use graphical environment that enables users to control operations with menu-driven commands.

20. DBMS Components • Schema • 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 • For example, specific users, systems, or locations might be permitted to create, retrieve, update, or delete data, depending on their needs and the company’s security policies

21. 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 • ODBC – open database connectivity • JDBC – Java database connectivity

22. Web-Based Database Design • The following sections discuss the characteristics of Web-based design, Internet terminology, connecting a database to the Web, and data security on the Web

23. 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

24. Web-Based Database Design • Internet Terminology • Web browser • Web page • HTML (Hypertext Markup Language) • Tags • Web server • Web site

25. Web-Based Database Design • Internet Terminology • Intranet • Extranet • Protocols • Web-centric • Clients • Servers

26. Web-Based Database Design • Connecting a Database to the Web • Database must be connected to the Internet or intranet • The database and the Internet speak two different languages • Middleware • Adobe ColdFusion

27. Web-Based Database Design • Data Security • Web-based data must be 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

28. Data Design Terminology • Definitions • Entity • Table or file • Field • Attribute • Common field • Record • Tuple

29. Data Design Terminology • Key Fields • Primary key • Combination key • Composite key • Concatenated key • Multi-valued key

30. Data Design Terminology • Key Fields • Candidate key • Nonkey field • Foreign key • Secondary key

31. Data Design Terminology • Referential Integrity • Validity checks can help avoid data input errors • In a relational database, referential integrity means that a foreign key value cannot be entered in one table unless it matches an existing primary key in another table • Orphan

32. Entity-Relationship Diagrams • An entity is a person, place, thing, or event for which data is collected and maintained • Entity-relationship diagram (ERD) • An ERD provides an overall view of the system, and a blueprint for creating the physical data structures

33. 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 • A popular method is to represent entities as rectangles and relationships as diamond shapes

34. Entity-Relationship Diagrams • Types of Relationships • Three types of relationships can exist between entities • One-to-one relationship (1:1) • One-to-many relationship (1:M) • Many-to-many relationship (M:N) • Associative entity

35. Entity-Relationship Diagrams • Cardinality • Cardinality notation • Crow’s foot notation • Unified Modeling Language (UML) • Now that you understand database elements and their relationships, you can start designing tables

36. Normalization • 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

37. 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)

38. Normalization • Repeating Groups and Unnormalized Design • Repeating group • Often occur in manual documents prepared by users • Unnormalized • Enclose the repeating group of fields within a second set of parentheses

39. 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

40. Normalization • Second Normal Form • To understand second normal form (2NF), you must understand the concept of functional dependence • Field X is functionally dependenton field Y if the value of field X depends on the value of field Y

41. Normalization • Second Normal Form • A standard process exists for converting a table from 1NF to 2NF • First, create and name a separate table for each field in the existing primary key • Next, create a new table for each possible combination of the original primary key fields • Finally, study the three tables and place each field with its appropriate primary key

42. Normalization • Second Normal Form • Four kinds of problems are found with 1NF description that do not exist with 2NF • 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

43. Normalization • Third Normal Form • 3NF design avoids redundancy and data integrity problems that still can exist in 2NF designs • 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

44. Normalization • Third Normal Form • 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

45. Normalization • A Normalization Example • To show the normalization process, consider the familiar situation in Figure 9-27 which might depict several entities in a school advising system: ADVISOR, COURSE, and STUDENT

46. Using Codes During System Design • Overview of Codes • A code is a set of letters or numbers that represents a data item. Codes can be used to simplify output, input, and data formats. • Because codes often are used to represent data, you encounter them constantly in your everyday life • They save storage space and costs, reduce data transmission time, and decrease data entry time • Can reduce data input errors

47. Using Codes During System Design • Types of Codes • [1] Sequence codes • Numbers/letters assigned in a specific order • E.g. UiTM student matric number • [2] Block sequence codes • Block sequence codes use blocks of numbers for different classifications. • E.g. course codes • 1xx – 3xx : diploma courses • 4xx – 6xx : bachelor courses • 7xx – 8xx : master courses

48. Using Codes During System Design • Types of Codes • [3] Alphabetic codes • [a] Category codes – identify related items using numbers/letters • E.g. ITS – system science courses, ITT – data comm. & networking courses, ITC – comp. science courses, ACC – accounting courses • [b] Abbreviation codes – mnemonic codes/abbreviations • E.g MY = Malaysia, SG = Singapore, NZ = New Zealand

49. Using Codes During System Design • Types of codes • [4] Significant digit codes - Distinguish items by using a series of subgroups of digits • E.g. Classroom number in UiTM Pahang: J1-01, J1-02, A1-01, A2-01 • [5] Derivation codes - Combine data from different item attributes/characteristics to build the code • E.g. Magazine release num: 201109.Vol.18 (Vol. 18, Released on September 2011) • Cipher codes • Action codes

50. Using Codes During System Design • Types of codes • [6] Cipher codes: use a keyword to encode a number • E.g. E.g. IASETTO = 1453770 • [7] Action codes - Indicate action to be executed associated with item • E.g. X – exit program, F – File menu