Transcript Chapter 9

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
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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
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Introduction
• Begins with a review of data design concepts
and terminology, then discusses file-based
systems and database systems, including Webbased 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
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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)
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Data Design Concepts
• Overview of File
Processing
– File processing can be
efficient and costeffective in certain
situations
– Potential problems
• Data redundancy
• Data integrity
• Rigid data structure
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Data Design Concepts
• Overview of File Processing
– Various types of files
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Master file
Table file
Transaction file
Work file
Security file
History file
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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
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Data Design Concepts
• The Evolution from File Systems to Database
Systems
– Some Advantages
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Scalability
Better support for client/server systems
Economy of scale
Flexible data sharing
Enterprise-wide application – database administrator
(DBA)
• Stronger standards
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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
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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
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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
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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
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Web-Based Database Design
• Characteristics of Web-Based Design
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Web-Based Database Design
• Internet Terminology
– Web browser
– Web page
– HTML (Hypertext Markup Language)
– Tags
– Web server
– Web site
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Web-Based Database Design
• Internet Terminology
– Intranet
– Extranet
– Protocols
– Web-centric
– Clients
– Servers
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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
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Data Design Terminology
• Definitions
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Entity
Table or file
Field
Record
• Tuple
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Data Design Terminology
• Key Fields
– Primary key
– Candidate key
– Foreign key
– Secondary key
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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
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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
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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)
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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
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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)
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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
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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
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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
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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
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Normalization
• A Normalization Example
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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
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Using Codes During Data Design
• Types of Codes
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Sequence codes
Block sequence codes
Alphabetic codes
Significant digit codes
Derivation codes
Cipher codes
Action codes
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Using Codes During Data Design
• Developing a Code
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Keep codes concise
Allow for expansion
Keep codes stable
Make codes unique
Use sortable codes
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Using Codes During Data Design
• Developing a Code
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Avoid confusing codes
Make codes meaningful
Use a code for a single purpose
Keep codes consistent
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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
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Database Models
• A Real-World Business
Example
– Imagine a company that
provides on-site service
for electronic
equipment, including
parts and labor
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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
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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
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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
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Data Storage and Access
• Data Coding and
Storage
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Binary digits
Bit
Byte
EBCDIC, ASCII, and
Binary
– Unicode
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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
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Data Control
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User ID
Password
Permissions
Encryption
Backup
Recovery procedures
Audit log files
Audit fields
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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
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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
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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
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Chapter Summary
• Chapter 9 complete
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