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Systems Analysis and Design
9th Edition
Chapter 9
Data Design
Chapter Objectives
• Explain file-oriented systems and how they differ
from database management systems
• 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
2
Chapter Objectives
• Explain the importance of codes and describe
various coding schemes
• Explain data warehousing and data mining
• Differentiate between logical and physical
storage and records
• Explain data control measures
3
Introduction
• 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
4
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
– Database management
system (DBMS)
5
Data Design Concepts
• Overview of File
Processing
– File processing can be
efficient and cost-
effective in certain
situations
– Potential problems
• Data redundancy
• Data integrity
• Rigid data structure
6
Data Design Concepts
• Overview of File Processing
– Various types of files
• Master file
• Table file
• Transaction file
• Work file
• Security file
• History file
7
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, acce
ss, and analyze the
contents of a database
– The main advantage of a
DBMS is that it offers
timely, interactive, and
flexible data access
8
Data Design Concepts
• The Evolution from File Systems to Database
Systems
– Some Advantages
• Scalability
• Better support for client/server systems
• Economy of scale
• Flexible data sharing
• Enterprise-wide application – database administrator
(DBA)
• Stronger standards
9
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
10
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
11
DBMS Components
• Data Manipulation Language
– A data manipulation language (DML) controls
database operations, including
storing, retrieving, updating, and deleting data
• 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
12
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
13
Web-Based Database Design
• Characteristics of Web-Based Design
14
Web-Based Database Design
• Internet Terminology
– Web browser
– Web page
– HTML (Hypertext Markup Language)
– Tags
– Web server
– Web site
15
Web-Based Database Design
• Internet Terminology
– Intranet
– Extranet
– Protocols
– Web-centric
– Clients
– Servers
16
Web-Based Database Design
• Connecting a Database to the Web
– Database must be connected to the Internet or
intranet
– Middleware
• Adobe ColdFusion
• Data Security
– 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
– Table or file
– Field
– Record
• Tuple
18
Data Design Terminology
• Key Fields
– Primary key
– Candidate key
– Foreign key
– Secondary key
19
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
20
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
21
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)
22
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
23
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)
24
Normalization
• Repeating Groups and Unnormalized Design
– Repeating groups
• Often occur in manual documents prepared by users
– Unnormalized
– Enclose the repeating group of fields within a
second set of parentheses
25
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
26
Normalization
• Second Normal Form
– A table design is in second normal form (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
– A standard process exists for converting a table from
1NF to 2NF
– The objective is to break the original table into two or
more new tables and reassign the fields so that each
nonkey field will depend on the entire primary key in
its table
27
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
– 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
28
Normalization
• A Normalization Example
29
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 data
transmission time, and decrease data entry time
– Can reduce data input errors
30
Using Codes During Data Design
• Types of Codes
1. Sequence codes
2. Block sequence codes
3. Alphabetic codes
4. Significant digit codes
5. Derivation codes
6. Cipher codes
7. Action codes
31
Using Codes During Data Design
• Developing a Code
1. Keep codes concise
2. Allow for expansion
3. Keep codes stable
4. Make codes unique
5. Use sortable codes
32
Using Codes During Data Design
• Developing a Code
6. Avoid confusing codes
7. Make codes meaningful
8. Use a code for a single purpose
9. Keep codes consistent
33
Database Design: One Step At a
Time
1. Create an initial ERD
2. Next, create an ERD
3. Review all the data elements
4. Review the 3NF designs for all tables
5. Double-check all data dictionary entries
• After creating your final ERD and normalized
table designs, you can transform them into a
database
34
Database Models
• A Real-World Business
Example
– Imagine a company that
provides on-site service
for electronic
equipment, including
parts and labor
35
Database Models
• Working with a Relational Database
– To understand the power and flexibility of a
relational database, try the following exercise
– Suppose you work in IT, and the sales team needs
answers to three specific questions
– The data might be stored physically in seven tables
36
Data Storage and Access
• Data storage and access
involve strategic
business tools
• Strategic tools for data
storage and access
– Data warehouse –
dimensions
– Data mart
– Data Mining
37
Data Storage and Access
• Logical and Physical Storage
– Logical storage
• Characters
• Data element or data item
• Logical record
– Physical storage
• Physical record or block
• Buffer
• Blocking factor
38
Data Storage and Access
• Data Coding and
Storage
– Binary digits
– Bit
– Byte
– EBCDIC, ASCII, and
Binary
– Unicode
39
Data Storage and Access
• Data Coding and Storage
– Storing dates
• Y2K Issue
• Most date formats now are based on the model
established by the International Organization for
Standardization (ISO)
• Absolute date
40
Data Control
• User ID
• Password
• Permissions
• Encryption
• Backup
• Recovery procedures
• Audit log files
• Audit fields
41
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
42
Chapter Summary
• An entity-relationship (ERD) is a graphic
representation of all system entities and the
relationships among them
• A code is a set of letters or numbers used to
represent data in a system
• The most common database models are
relational and object-oriented
43
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
44
Chapter Summary
• Chapter 9 complete
45

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Systems Analysis and Design Chapter 9 Data Design

  • 1. Systems Analysis and Design 9th Edition Chapter 9 Data Design
  • 2. Chapter Objectives • Explain file-oriented systems and how they differ from database management systems • 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 2
  • 3. Chapter Objectives • Explain the importance of codes and describe various coding schemes • Explain data warehousing and data mining • Differentiate between logical and physical storage and records • Explain data control measures 3
  • 4. Introduction • 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 4
  • 5. 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 – Database management system (DBMS) 5
  • 6. Data Design Concepts • Overview of File Processing – File processing can be efficient and cost- effective in certain situations – Potential problems • Data redundancy • Data integrity • Rigid data structure 6
  • 7. Data Design Concepts • Overview of File Processing – Various types of files • Master file • Table file • Transaction file • Work file • Security file • History file 7
  • 8. 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, acce ss, and analyze the contents of a database – The main advantage of a DBMS is that it offers timely, interactive, and flexible data access 8
  • 9. Data Design Concepts • The Evolution from File Systems to Database Systems – Some Advantages • Scalability • Better support for client/server systems • Economy of scale • Flexible data sharing • Enterprise-wide application – database administrator (DBA) • Stronger standards 9
  • 10. 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 10
  • 11. 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 11
  • 12. DBMS Components • Data Manipulation Language – A data manipulation language (DML) controls database operations, including storing, retrieving, updating, and deleting data • 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 12
  • 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 – ODBC – open database connectivity – JDBC – Java database connectivity 13
  • 14. Web-Based Database Design • Characteristics of Web-Based Design 14
  • 15. Web-Based Database Design • Internet Terminology – Web browser – Web page – HTML (Hypertext Markup Language) – Tags – Web server – Web site 15
  • 16. Web-Based Database Design • Internet Terminology – Intranet – Extranet – Protocols – Web-centric – Clients – Servers 16
  • 17. Web-Based Database Design • Connecting a Database to the Web – Database must be connected to the Internet or intranet – Middleware • Adobe ColdFusion • Data Security – 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
  • 18. Data Design Terminology • Definitions – Entity – Table or file – Field – Record • Tuple 18
  • 19. Data Design Terminology • Key Fields – Primary key – Candidate key – Foreign key – Secondary key 19
  • 20. 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 20
  • 21. 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 21
  • 22. 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) 22
  • 23. 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 23
  • 24. 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) 24
  • 25. Normalization • Repeating Groups and Unnormalized Design – Repeating groups • Often occur in manual documents prepared by users – Unnormalized – Enclose the repeating group of fields within a second set of parentheses 25
  • 26. 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 26
  • 27. Normalization • Second Normal Form – A table design is in second normal form (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 – A standard process exists for converting a table from 1NF to 2NF – The objective is to break the original table into two or more new tables and reassign the fields so that each nonkey field will depend on the entire primary key in its table 27
  • 28. 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 – 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 28
  • 30. 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 data transmission time, and decrease data entry time – Can reduce data input errors 30
  • 31. Using Codes During Data Design • Types of Codes 1. Sequence codes 2. Block sequence codes 3. Alphabetic codes 4. Significant digit codes 5. Derivation codes 6. Cipher codes 7. Action codes 31
  • 32. Using Codes During Data Design • Developing a Code 1. Keep codes concise 2. Allow for expansion 3. Keep codes stable 4. Make codes unique 5. Use sortable codes 32
  • 33. Using Codes During Data Design • Developing a Code 6. Avoid confusing codes 7. Make codes meaningful 8. Use a code for a single purpose 9. Keep codes consistent 33
  • 34. Database Design: One Step At a Time 1. Create an initial ERD 2. Next, create an ERD 3. Review all the data elements 4. Review the 3NF designs for all tables 5. Double-check all data dictionary entries • After creating your final ERD and normalized table designs, you can transform them into a database 34
  • 35. Database Models • A Real-World Business Example – Imagine a company that provides on-site service for electronic equipment, including parts and labor 35
  • 36. Database Models • Working with a Relational Database – To understand the power and flexibility of a relational database, try the following exercise – Suppose you work in IT, and the sales team needs answers to three specific questions – The data might be stored physically in seven tables 36
  • 37. Data Storage and Access • Data storage and access involve strategic business tools • Strategic tools for data storage and access – Data warehouse – dimensions – Data mart – Data Mining 37
  • 38. Data Storage and Access • Logical and Physical Storage – Logical storage • Characters • Data element or data item • Logical record – Physical storage • Physical record or block • Buffer • Blocking factor 38
  • 39. Data Storage and Access • Data Coding and Storage – Binary digits – Bit – Byte – EBCDIC, ASCII, and Binary – Unicode 39
  • 40. Data Storage and Access • Data Coding and Storage – Storing dates • Y2K Issue • Most date formats now are based on the model established by the International Organization for Standardization (ISO) • Absolute date 40
  • 41. Data Control • User ID • Password • Permissions • Encryption • Backup • Recovery procedures • Audit log files • Audit fields 41
  • 42. 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 42
  • 43. Chapter Summary • An entity-relationship (ERD) is a graphic representation of all system entities and the relationships among them • A code is a set of letters or numbers used to represent data in a system • The most common database models are relational and object-oriented 43
  • 44. 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 44