Transcript Ch_7_mod

c h a p t e r
7
MANAGING
DATA
RESOURCES
7.1
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LEARNING OBJECTIVES
• COMPARE TRADITIONAL FILE
ORGANIZATION & MANAGEMENT
TECHNIQUES
• DESCRIBE HOW DATABASE
MANAGEMENT SYSTEM
ORGANIZES INFORMATION
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7.2
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LEARNING OBJECTIVES
• IDENTIFY TYPES OF DATABASE,
PRINCIPLES OF DATABASE DESIGN
• DISCUSS DATABASE TRENDS
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7.3
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MANAGEMENT CHALLENGES
• TRADITIONAL DATA FILE
ENVIRONMENT
• DATABASE APPROACH TO DATA
MANAGEMENT
• CREATING DATABASE
ENVIRONMENT
• DATABASE TRENDS
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7.4
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MANAGEMENT CHALLENGES
1. ORGANIZATIONAL OBSTACLES:
Challenges existing power structure,
requires organizational restructure
2. COST / BENEFIT CONSIDERATIONS:
Large initial costs, delayed benefits,
tangible, intangible
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7.5
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PROBLEMS WITH TRADITIONAL FILE
ENVIRONMENT
•
•
•
•
•
7.6
DATA REDUNDANCY
PROGRAM / DATA DEPENDENCY
LACK OF FLEXIBILITY
POOR SECURITY
Flat File
LACK OF DATA
SHARING &
AVAILABILITY
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FILING METHODS
• INDEXED SEQUENTIAL ACCESS METHOD (ISAM) :
– EACH RECORD IDENTIFIED BY KEY
– GROUPED IN BLOCKS AND CYLINDERS
– KEYS IN INDEX
• VIRTUAL STORAGE ACCESS METHOD (VSAM) :
– MEMORY DIVIDED INTO AREAS & INTERVALS
– DYNAMIC FILE SPACE
VSAM WIDELY USED FOR RELATIONAL
DATABASES
• DIRECT FILE ACCESS METHOD
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7.7
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DIRECT FILE ACCESS METHOD
• EACH RECORD HAS KEY FIELD
• KEY FIELD FED INTO TRANSFORM
ALGORITHM
• ALGORITHM GENERATES PHYSICAL
STORAGE LOCATION OF RECORD
(RECORD ADDRESS)
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7.8
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DATABASE MANAGEMENT SYSTEM (DBMS)
SOFTWARE TO CREATE & MAINTAIN
DATA
ENABLES BUSINESS APPLICATIONS
TO EXTRACT DATA
INDEPENDENT OF SPECIFIC
COMPUTER PROGRAMS
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7.9
DBMS
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COMPONENTS OF DBMS:
• DATA DEFINITION LANGUAGE:
– Defines data elements in database
• DATA MANIPULATION LANGUAGE:
– Manipulates data for applications
• DATA DICTIONARY:
– Formal definitions of all variables in
database, controls variety of database
contents, data elements
7.10
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DBMS
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STRUCTURED QUERY LANGUAGE (SQL)
EMERGING STANDARD
DATA MANIPULATION LANGUAGE
FOR RELATIONAL DATABASES
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7.11
DBMS
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ELEMENTS OF SQL
• SELECT: List of columns from tables
desired
• FROM: Identifies tables from which
columns will be selected
• WHERE: Includes conditions for
selecting specific rows, conditions
for joining multiple tables
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7.12
DBMS
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TWO VIEWS OF DATA
• PHYSICAL VIEW: Where is data physically?
– DRIVE, DISK, SURFACE, TRACK, SECTOR
(BLOCK), RECORD
– TAPE, BLOCK, RECORD NUMBER (KEY)
• LOGICAL VIEW: What data is needed by
application?
– SUCCESSION OF FACTS NEEDED BY
APPLICATION
– NAME, TYPE, LENGTH OF FIELD
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7.13
DBMS
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RELATIONAL DATA MODEL
•
•
•
•
7.14
DATA IN TABLE FORMAT
RELATION: TABLE
TUPLE: ROW (RECORD) IN TABLE
FIELD: COLUMN (ATTRIBUTE) IN TABLE
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HOURS
RATE
TOTAL
ABLE
$ 40.50 $ 10.35 $ 419.18
BAXTER $ 38.00 $ 8.75 $ 332.50
CHEN
$ 42.70 $ 9.25 $ 394.98
DENVER $ 35.90 $ 9.50 $ 341.05
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TYPES OR RELATIONS
ONE-TO-ONE:
STUDENT
CLASS
ONE-TO-MANY:
STUDENT
A
MANY-TO-MANY:
STUDENT
B
CLASS
1
STUDENT
A
7.15
ID
STUDENT
C
CLASS
2
STUDENT
B
STUDENT
C
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HIERARCHICAL DATA MODEL
ROOT
FIRST
CHILD
2nd
CHILD
7.16
Employer
Compensation
Ratings
Salary
Job
Assignments
Pension
Benefits
Insurance
Health
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NETWORK DATA MODEL
• VARIATION OF HIERARCHICAL
MODEL
• USEFUL FOR MANY-TO-MANY
RELATIONSHIPS
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NETWORK
1
NETWORK
A
7.17
NETWORK
2
NETWORK
B
NETWORK
C
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OTHER SYSTEMS
• LEGACY SYSTEM: older system
• OBJECT - ORIENTED DBMS: stores
data & procedures as objects
• OBJECT - RELATIONAL DBMS:
hybrid
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7.18
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CREATING A DATABASE
• CONCEPTUAL DESIGN
• PHYSICAL DESIGN
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7.19
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CREATING A DATABASE
CONCEPTUAL DESIGN:
• ABSTRACT MODEL, BUSINESS
PERSPECTIVE
• HOW WILL DATA BE GROUPED?
• RELATIONSHIPS AMONG
ELEMENTS
• ESTABLISH END-USER
NEEDS
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7.20
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CREATING A DATABASE
PHYSICAL DESIGN:
• DETAILED MODEL BY DATABASE
SPECIALISTS
• ENTITY-RELATIONSHIP DIAGRAM
• NORMALIZATION
• HARDWARE / SOFTWARE
SPECIFIC
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7.21
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ELEMENTS OF DATABASE
ENVIRONMENT
DATA
DATABASE
TECHNO
LOGY &
MANAGEMENT
ADMINISTRATION
DATABASE
MANAGEMENT
SYSTEM
DATA PLANNING
& MODELING
METHODOLOGY
7.22
USERS
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ENTITY- RELATIONSHIP DIAGRAM
ORDER
ORDER: #, DATE, PART #, QUANTITY
1
CAN
HAVE
1
PART: #, DESCRIPTION, UNIT PRICE,
SUPPLIER #
PART
M
CAN
HAVE
1
SUPPLIER
7.23
SUPPLIER: #, NAME,
ADDRESS
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NORMALIZATION
PROCESS OF CREATING SMALL DATA
STRUCTURES FROM COMPLEX
GROUPS OF DATA
EXAMPLES:
• ACCOUNTS RECEIVABLE
• PERSONNEL RECORDS
• PAYROLL
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7.24
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DISTRIBUTED DATABASES
7.25
• PARTITIONED: remote CPUs
(connected to host) have files unique
to that site, e.g., records on local
customers
• DUPLICATE: each remote CPU has
copies of common files,
e.g., layouts for standard
reports and forms
*
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DATABASE ADMINISTRATION
• DEFINES & ORGANIZES DATABASE
STRUCTURE AND CONTENT
• DEVELOPS SECURITY PROCEDURES
• DEVELOPS DATABASE DOCUMENTATION
• MAINTAINS DBMS
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7.26
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DATABASE TRENDS
• MULTIDIMENSIONAL DATA
ANALYSIS: 3D (or higher) groupings
to store complex data
• HYPERMEDIA: Nodes contain text,
graphics, sound, video,
programs. organizes
data as nodes.
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7.27
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DATABASE TRENDS
• DATA WAREHOUSE: Organization’s
electronic library stores consolidated
current & historic data for
management reporting & analysis
• ON-LINE ANALYTICAL PROCESSING
(OLAP): Tools for multidimensional data analysis
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7.28
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COMPONENTS OF DATA WAREHOUSE
OPERATIONAL,
HISTORICAL DATA
INTERNAL
DATA
SOURCES
DATA WAREHOUSE
DATA
ACCESS &
ANALYSIS
EXTRACT,
TRANSFORM
INFORMATION
DIRECTORY
EXTERNAL
DATA
SOURCES
7.29
QUERIES &
REPORTS
OLAP
DATA MINING
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DATABASE TRENDS
• DATA MART: Small data warehouse
for special function, e.g.,
Focused marketing based
on customer info
• DATAMINING: Tools for finding
hidden patterns, relationships, for predicting trends
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7.30
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DATABASE TRENDS
LINKING DATABASES TO THE WEB:
• WEB USER CONNECTS TO VENDOR
DATABASE
• SPECIAL SOFTWARE CONVERTS
HTML TO SQL
• SQL FINDS DATA, SERVER
CONVERTS RESULT TO
HTML
7.31
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c h a p t e r
7
MANAGING
DATA
RESOURCES
7.32
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