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Transcript
Systems Analysis & Design
5th Edition
Chapter 6
Data Design
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
2
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
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
4
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
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
mining, data warehousing, 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-oriented and
database systems, including Web-based
database design
7
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
8
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
9
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
10
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
11
Data Design Concepts
● Overview of Database Systems
12
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
13
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
14
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
15
DBMS Components
● A DBMS provides an interface between a
database and users who need to access the
data
16
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
17
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
18
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
19
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
20
Web-Based Database Design
● Internet Terminology
–
–
–
–
–
–
Web browser
Web page
HTML – Hypertext Markup Language
Web server
Web site
Intranet
21
Web-Based Database Design
● Internet Terminology
–
–
–
–
–
Extranet
Protocols
Web-centric
Clients
Servers
22
Web-Based Database Design
● Connecting a Database to the Web
– Database must be connected to the Internet or
intranet
• Middleware
• Macromedia’s ColdFusion
23
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
24
Data Design Terminology
● Definitions
–Entity
–Table or file
–Field
• Attribute - Common field
–Record
• Tuple
25
Data Design Terminology
● Key Fields
– Primary key
•
•
•
•
Combination key
Composite key
Concatenated key
Multi-valued key
– Candidate key
• Nonkey field
– Foreign key
– Secondary key
26
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
27
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)
28
Data Relationships
● Entity-Relationship Diagrams
29
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
30
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)
31
Normalization
● Repeating Groups and Unnormalized
Design
–Repeating group
• Often occur in manual documents prepared by users
–Unnormalized design
32
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
33
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
34
Normalization
● Second Normal Form
–
A standard process exists for converting a
table from 1NF to 2NF
1. Create and name a separate table for each field in
the existing primary key
2. Create a new table for each possible combination
of the original primary key fields
3. Study the three tables and place each field with its
appropriate primary key
35
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
36
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
37
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
38
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
39
Steps in Database Design
1. Create the initial ERD
2. Assign all data elements to entities
3. Create 3NF designs for all tables, taking
care to identify all primary, secondary,
and foreign keys
4. Verify all data dictionary entries
● After creating your final ERD and
normalized table designs, you can
transform them into a database
40
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
41
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
42
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
43
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
44
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
45
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
46
Data Storage
● Data Storage Formats
–
–
–
–
–
Binary digits
Bit
Byte
EBCDIC and ASCII
Unicode
47
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
48
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
49
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
50
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 builtin control and security features, including
subschemas, passwords, encryption, audit
trail files, and backup and recovery
procedures to maintain data
51
Data Control
●
●
●
●
●
●
●
User ID
Password
Backup
Recovery procedures
Audit log files
Audit fields
Encryption
52
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
53
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
54
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
55
Systems Analysis & Design
5th Edition
Chapter 6 Complete