Download The Database Environment

CHAPTER 1:
THE DATABASE ENVIRONMENT AND
DEVELOPMENT PROCESS
Modern Database Management
11th Edition
Jeffrey A. Hoffer, V. Ramesh,
Heikki Topi
© 2013 Pearson Education, Inc. Publishing as Prentice Hall
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INCENTIVE TO PAY ATTENTION
Salaries and current jobs available for
database professionals www.payscale.com
 Database Analyst (39,512 – 88,354) Median –
56,884
 This is non-specific; I just gathered the average,
high and low for this job title. Feel free to go to
the site, put in more detailed information, and
see what’s available.

Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall
INCENTIVE TO PAY ATTENTION
Your ability to manage stuff (things, people,
customer relationships, etc…) is dependent on
your ability to keep track of data about it
 Your ability to keep track of data is dependent
on your ability to find it
 Your ability to find your data is dependent on
how well you store it
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Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall
OBJECTIVES
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Define terms
Name limitations of conventional file processing
Explain advantages of databases
Identify costs and risks of databases
List components of database environment
Identify categories of database applications
Describe database system development life cycle
Explain prototyping and agile development approaches
Explain roles of individuals
Explain the three-schema architecture for databases
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DEFINITIONS
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Database: organized collection of logically related data
Data: stored representations of meaningful objects and
events
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Structured: numbers, text, dates
Unstructured: images, video, documents
Information: data processed to increase knowledge in
the person using the data
Metadata: data that describes the properties and
context of user data
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Figure 1-1a Data in context
Context helps users understand data
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Figure 1-1b Summarized data
Graphical displays turn data into useful
information that managers can use for
decision making and interpretation
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Descriptions of the properties or characteristics of the
data, including data types, field sizes, allowable
values, and data context
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DISADVANTAGES OF FILE PROCESSING
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Program-Data Dependence
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Duplication of Data
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No centralized control of data
Lengthy Development Times
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Different systems/programs have separate copies of the same data
Limited Data Sharing
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All programs maintain metadata for each file they use
Programmers must design their own file formats
Excessive Program Maintenance
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80% of information systems budget
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PROBLEMS WITH DATA DEPENDENCY
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Each application programmer must maintain
his/her own data
Each application program needs to include code
for the metadata of each file
Each application program must have its own
processing routines for reading, inserting,
updating, and deleting data
Lack of coordination and central control
Non-standard file formats
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DATABASE VS FILE SYSTEMS
Traditional File System
Program 1
Meta-Data
Data
Program 2
Meta-Data
Data
Program 3
Meta-Data
Data
Program 1
Program 2
Database Management System
Meta-Data
Data
Program 3
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Duplicate Data
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PROBLEMS WITH DATA REDUNDANCY
 Waste
of space to have duplicate data
 Causes more maintenance headaches
 The biggest problem:
 Data
changes in one file could cause
inconsistencies
 Compromises in data integrity
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SOLUTION: THE DATABASE APPROACH
 Central
repository of shared data
 Data is managed by a controlling agent
 Stored in a standardized, convenient
form
Requires a Database Management System (DBMS)
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DATABASE MANAGEMENT SYSTEM

A software system that is used to create, maintain, and provide
controlled access to user databases
Order Filing
System
Invoicing
System
Payroll
System
DBMS
Central database
Contains employee,
order, inventory,
pricing, and
customer data
DBMS manages data resources like an operating system manages hardware resources
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ADVANTAGES OF THE DATABASE
APPROACH
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Program-data independence
Planned data redundancy
Improved data consistency
Improved data sharing
Increased application development productivity
Enforcement of standards
Improved data quality
Improved data accessibility and responsiveness
Reduced program maintenance
Improved decision support
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NO FREE LUNCHES
New, specialized personnel
 Installation and management cost and
complexity
 Conversion costs
 Need for explicit backup and recovery
 Organizational conflict
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ELEMENTS OF THE DATABASE APPROACH
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Data models
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Entities
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Noun form describing a person, place, object, event, or concept
Composed of attributes
Relationships
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Graphical system capturing nature and relationship of data
Enterprise Data Model–high-level entities and relationships for the organization
Project Data Model–more detailed view, matching data structure in database or
data warehouse
Between entities
Usually one-to-many (1:M) or many-to-many (M:N)
Relational Databases

Database technology involving tables (relations) representing entities and
primary/foreign keys representing relationships
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Figure 1-3 Comparison of enterprise and project level data models
Segment of an enterprise data model
Segment of a project-level data model
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One customer
may place many
orders, but each
order is placed by
a single customer
 One-to-many
relationship
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One order has many
order lines; each order
line is associated with
a single order
 One-to-many
relationship
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One product can
be in many
order lines, each
order line refers
to a single
product
 One-to-many
relationship
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Therefore, one
order involves
many products
and one product is
involved in many
orders
 Many-to-many
relationship
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FOREIGN (LINKING) KEYS
Relationships established in special columns that
provide links between tables
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Figure 1-5 Components of the Database Environment
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APPLICATION PROGRAM FUNCTIONS
Create new records
(inserting new data)
 Read data for
display
 Updating existing
data
 Deleting existing
data
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Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall
COMPONENTS OF THE DATABASE ENVIRONMENT
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CASE Tools–computer-aided software engineering
Repository–centralized storehouse of metadata
Database Management System (DBMS) –software for
managing the database
Database–storehouse of the data
Application Programs–software using the data
User Interface–text and graphical displays to users
Data/Database Administrators–personnel responsible for
maintaining the database
System Developers–personnel responsible for designing
databases and software
End Users–people who use the applications and databases
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DOCUMENTATION
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most formal development methodologies are
documentation based
helps managers monitor progress and quality of
project
facilitates communication between team members
includes models
various stages are not complete until documentation
is accepted
Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall
SOME KEYS TO SUCCESS...
accurate requirements definition
 commitment
 effective change management
 manageable size
 champion
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FIGURE 1-6 Example business function-to-data entity matrix
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2 APPROACHES TO DEVELOP DATABASE & IS
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SDLC
System Development Life Cycle
 Detailed, well-planned development process
 Time-consuming, but comprehensive
 Long development cycle
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Prototyping
Rapid application development (RAD)
 Cursory attempt at conceptual data modeling
 Define database during development of initial prototype
 Repeat implementation and maintenance activities with
new prototype versions
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SYSTEMS DEVELOPMENT LIFE CYCLE
(SEE ALSO FIGURE 1-7)
Planning
Analysis
Logical Design
Physical Design
Implementation
Maintenance
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SYSTEMS DEVELOPMENT LIFE CYCLE
(SEE ALSO FIGURE 1-7) (CONT.)
Purpose–preliminary understanding
Deliverable–request for study
Planning
Planning
Analysis
Logical Design
Physical Design
Database activity–
enterprise modeling and
early conceptual data
modeling
Implementation
Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Maintenance
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SYSTEMS DEVELOPMENT LIFE CYCLE
(SEE ALSO FIGURE 1-7) (CONT.)
Purpose–thorough requirements analysis and
structuring
Deliverable–functional system specifications
Planning
Analysis
Analysis
Logical Design
Physical Design
Database activity–thorough
and integrated conceptual
data modeling
Implementation
Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Maintenance
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SYSTEMS DEVELOPMENT LIFE CYCLE
(SEE ALSO FIGURE 1-7) (CONT.)
Purpose–information requirements elicitation
and structure
Deliverable–detailed design specifications
Planning
Analysis
Logical Design
Logical
Design
Physical Design
Database activity–
logical database design
(transactions, forms,
displays, views, data
integrity and security)
Implementation
Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Maintenance
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SYSTEMS DEVELOPMENT LIFE CYCLE
(SEE ALSO FIGURE 1-7) (CONT.)
Purpose–develop technology and
organizational specifications
Planning
Deliverable–program/data
structures, technology purchases,
organization redesigns
Analysis
Logical Design
Physical
Design
Physical Design
Database activity–
physical database design (define
database to DBMS, physical
data organization, database
processing programs)
Implementation
Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Maintenance
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SYSTEMS DEVELOPMENT LIFE CYCLE
(SEE ALSO FIGURE 1-7) (CONT.)
Purpose–programming, testing,
training, installation, documenting
Planning
Analysis
Deliverable–operational programs,
documentation, training materials
Logical Design
Physical Design
Database activity–
database implementation,
including coded programs,
documentation,
installation and conversion
Implementation
Implementation
Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Maintenance
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SYSTEMS DEVELOPMENT LIFE CYCLE
(SEE ALSO FIGURE 1-7) (CONT.)
Purpose–monitor, repair, enhance
Planning
Deliverable–periodic audits
Analysis
Logical Design
Physical Design
Database activity–
database maintenance,
performance analysis
and tuning, error
corrections
Implementation
Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Maintenance
Maintenance
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DATABASE SDLC
SDLC
Database Development
Activities
Identify Project
Initiate and Plan
Analyze
Logical Design
Physical Design
Implementation
Maintenance
Enterprise
Modeling
Conceptual
Data Modeling
Logical
DB Design
Physical DB
Design/Creation
DB
Implementation
DB
Maintenance
Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall
ENTERPRISE DATA MODEL
First step in the database development process
 Specifies scope and general content
 Overall picture of organizational data at high
level of abstraction
 Entity-relationship diagram
 Descriptions of entity types
 Relationships between entities
 Business rules
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PLANNING MATRIXES
 Show
interrelationships between objects.
 Location-to-Function
 Unit-to-Function
 Information
System-to-Data Entity
 Supporting Function-to-Data Entity
 Information System-to-Objective
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BUSINESS FUNCTION-TO-DATA ENTITY PLANNING
MATRIX
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INFORMATION SYSTEM-TO-OBJECTIVE PLANNING
MATRIX
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FUNCTIONAL DECOMPOSITION
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ENTERPRISE DATA MODEL
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A model which includes:
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overall range of organizational
databases
general contents of organizational
databases
Built as part of IS planning for the
organization and not the design of
a particular database
One part of an organization’s overall
information systems architecture
(ISA)
Enterprise
Modeling
Conceptual
Data Modeling
Logical
DB Design
Physical DB
Design/Creation
DB
Implementation
DB
Maintenance
Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall
CONCEPTUAL DATABASE MODELING
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Determine user
requirements
Determine business rules
Build conceptual data
model
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outcome is an entityrelationship diagram or
similar communication
tool
population of repository
Enterprise
Modeling
Conceptual
Data Modeling
Logical
DB Design
Physical DB
Design/Creation
DB
Implementation
DB
Maintenance
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LOGICAL DATABASE DESIGN
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Select logical
database model
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commit to a database
alternative
Map EntityRelationship Diagrams
Normalize data
structures
Specify business rules
Enterprise
Modeling
Conceptual
Data Modeling
Logical
DB Design
Physical DB
Design/Creation
DB
Implementation
DB
Maintenance
Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall
PHYSICAL DATABASE DESIGN
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Select DBMS
Select storage devices
Determine access
methods
Design files and indexes
Determine database
distribution
Specify update strategies
Enterprise
Modeling
Conceptual
Data Modeling
Logical
DB Design
Physical DB
Design/Creation
DB
Implementation
DB
Maintenance
Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall
DATABASE IMPLEMENTATION
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Code and test
database processing
programs
Complete
documentation
Install database and
convert data
Enterprise
Modeling
Conceptual
Data Modeling
Logical
DB Design
Physical DB
Design/Creation
DB
Implementation
DB
Maintenance
Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall
DATABASE MAINTENANCE
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Analyze database and
applications to ensure
evolving information
requirements are being
met
Tune database for
improved performance
Fix errors
Provide data recovery
when needed
Enterprise
Modeling
Conceptual
Data Modeling
Logical
DB Design
Physical DB
Design/Creation
DB
Implementation
DB
Maintenance
Chapter 1 © 2013 Pearson Education, Inc. Publishing as Prentice Hall
Prototyping Database Methodology
(Figure 1-8)
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Prototyping Database Methodology
(Figure 1-8) (cont.)
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Prototyping Database Methodology
(Figure 1-8) (cont.)
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Prototyping Database Methodology
(Figure 1-8) (cont.)
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Prototyping Database Methodology
(Figure 1-8) (cont.)
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DATABASE SCHEMA
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External Schema
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Conceptual Schema
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User Views
Subsets of Conceptual Schema
Can be determined from business-function/data
entity matrices
DBA determines schema for different users
E-R models–covered in Chapters 2 and 3
Internal Schema
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Logical structures–covered in Chapter 4
Physical structures–covered in Chapter 5
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Figure 1-9 Three-schema architecture
Different people
have different
views of the
database…these
are the external
schema
The internal
schema is the
underlying
design and
implementation
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MANAGING PROJECTS
 Project–a
planned undertaking of
related activities to reach an objective
that has a beginning and an end
 Initiated and planned in planning stage
of SDLC
 Executed during analysis, design, and
implementation
 Closed at the end of implementation
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MANAGING PROJECTS:
PEOPLE INVOLVED
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Business analysts
Systems analysts
Database analysts and data modelers
Users
Programmers
Database architects
Data administrators
Project managers
Other technical experts
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EVOLUTION OF DATABASE SYSTEMS
 Driven
by four main objectives:
Need for program-data independence 
reduced maintenance
 Desire to manage more complex data
types and structures
 Ease of data access for less technical
personnel
 Need for more powerful decision support
platforms

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Figure 1-10a Evolution of database technologies
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Figure 1-10b Database architectures
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Figure 1-10b Database architectures (cont.)
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Figure 1-10b Database architectures (cont.)
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THE RANGE OF DATABASE
APPLICATIONS
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Personal databases
Two-tier and N-tier Client/Server databases
Enterprise applications
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Enterprise resource planning (ERP) systems
Data warehousing implementations
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Figure 1-11 Two-tier database with local
area network
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Figure 1-12 Three-tiered client/server database
architecture
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ENTERPRISE DATABASE APPLICATIONS
 Enterprise
Resource Planning (ERP)
 Integrate
all enterprise functions
(manufacturing, finance, sales, marketing,
inventory, accounting, human resources)
 Data
Warehouse
 Integrated
decision support system
derived from various operational
databases
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FIGURE 1-13 Computer
System for Pine Valley
Furniture Company
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THE BIG PICTURE
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