1. Chapter 6
Data Design

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 3

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 3

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 4

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 Physical Data Repository
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 format to 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 dependent on 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 database resembles 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

51. 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

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

53. Chapter Summary
Files and tables contain data about people, places, things, or events that affect the information system
DBMS designs are more powerful and flexible than traditional file-oriented systems 49

54. Chapter Summary
Data design tasks include creating an initial ERD; assigning data elements to an entity; normalizing all table designs; and completing the data dictionary entries for files, records, and data elements
The four basic database models are hierarchical, network, relational, and object-oriented 49

55. Chapter Summary
Logical storage is information seen through a user’s eyes, regardless of how or where that information actually is organized or stored
Physical storage is hardware-related and involves reading and writing blocks of binary data to physical media
File and database control measures include limiting access to the data, data encryption, backup/recovery procedures, audit-trail files, and internal audit fields 49

56. Chapter 6 Complete