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Chapter 6

Data Design. Chapter 6. Phase Description. Systems Design is the third of five phases in the systems development life cycle (SDLC) Now you are ready to begin the physical design of the system that will meet the specifications described in the system requirements document

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Chapter 6

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  1. Data Design Chapter 6

  2. Phase Description • Systems Design is the third of five phases in the systems development life cycle (SDLC) • Now you are ready to begin the physical design of the system that will meet the specifications described in the system requirements document • Systems design tasks include data design, user interface design, and system architecture

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

  4. 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 • Understand the steps in database design

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

  6. 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 mining, data warehousing, physical design issues, logical and physical records, data storage formats, and data controls

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

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

  9. Data Design Concepts • Overview of File Processing • Some companies use file processing to handle large volumes of structured data • Although less common today, file processing can be more efficient and cost less than a DBMS in certain situations

  10. Data Design Concepts • Overview of File Processing • Potential problems • Data redundancy • Data integrity • Rigid data structure • Uses various types of files • Master file • Table file • Transaction file • Work file – scratch file • Security file • History file

  11. Data Design Concepts • Overview of 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 • Overview of Database Systems

  13. Data Design Concepts • Overview of 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

  14. Data Design Concepts • Overview of Database Systems • Advantages • Scalability • 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

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

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

  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 • Data Manipulation Language • A data manipulation language (DML) controls database operations, including storing, retrieving, updating, and deleting data

  19. 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 • 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

  20. 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

  21. Web-Based Database Design • Internet Terminology • Web browser • Web page • HTML – Hypertext Markup Language • Web server • Web site • Intranet

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

  23. Web-Based Database Design • Connecting a Database to the Web • Database must be connected to the Internet or intranet • Middleware • Macromedia’s ColdFusion

  24. 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

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

  26. Data Design Terminology • Key Fields • Primary key • Combination key • Composite key • Concatenated key • Multi-valued key • Candidate key • Nonkey field • Foreign key • Secondary key

  27. 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

  28. Data Relationships • A relationship is a logical link between entities based on how they interact • Entity-Relationship Diagrams • One-to-one relationship (1:1) • One-to-many relationship (1:M) • Many-to-many relationship (M:N) • Cardinality • Cardinality notation • Crow’s foot notation • Unified Modeling Language (UML)

  29. Data Relationships • Entity-Relationship Diagrams

  30. 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

  31. 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)

  32. Normalization • Repeating Groups and Unnormalized Design • Repeating group • Often occur in manual documents prepared by users • Unnormalized design

  33. 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

  34. 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

  35. 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

  36. 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

  37. 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

  38. 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

  39. Normalization • A Normalization Example • To show the normalization process, consider the familiar situation in Figure 6-24 which might depict several entities in a school advising system: ADVISOR, COURSE, and STUDENT • The relationships among the three entities are shown in the ERD in Figure 6-25

  40. 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

  41. Database Models • Hierarchical and Network Databases • In a hierarchical database, data is organized like a family tree or organization chart, with branches representing parent records and child records • A network databaseresembles a hierarchical design, but provides somewhat more flexibility

  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

  43. Database Models • Object-Oriented Databases • Many systems developers are using object-oriented database (OODB) design as a natural extension of the object-oriented analysis process • Object Data Standard • Object Database Management Group (ODMG) • Each object has a unique object identifier

  44. Data Storage • Data Warehousing • Data warehouse - dimensions • Without a data warehouse it would be difficult for a user to extract data that spans several information systems and time frames • Allows users to retrieve and analyze the data easily

  45. Data Storage • Data Mining • Works best when you have clear, measurable goals • Increase average pages viewed per session • Increase number of referred customers • Reduce clicks to close • Increase checkouts per visit • Increase average profit per checkout

  46. Data Storage • Logical and Physical Storage • Logical storage • As seen through a user’s eyes • Characters • Date element or data item • Logical record • Physical storage • Hardware-related • Physical record or block • Blocking factor

  47. Data Storage • Data Storage Formats • Binary digits • Bit • Byte • EBCDIC and ASCII • Unicode

  48. Data Storage • Data Storage Formats • Binary • Binary storage format • Integer format • Long integer format • Other binary formats exist for efficient storage of exceedingly long numbers

  49. Data Storage • Selecting a Data Storage Format • In many cases, a user can select a specific data storage format • For example, when using Microsoft Office, you can store documents, spreadsheets, and databases in Unicode-compatible form by using the font called Arial Unicode MS • Selecting the right data storage format depends on the situation

  50. Data Storage • Date Fields • Most date formats now are based on the model established by the International Organization for Standardization (ISO) • Can be sorted easily and used in comparisons • Absolute date • Best method for storing date fields depends on how the specific date will be printed, displayed or used in a calculation

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