Weitere ähnliche Inhalte Ähnlich wie 009445185.pdf Ähnlich wie 009445185.pdf (20) Kürzlich hochgeladen (20) 009445185.pdf1. E. Wainright Martin Carol V. Brown Daniel W. DeHayes
Jeffrey A. Hoffer William C. Perkins
MANAGING
INFORMATION
TECHNOLOGY
FIFTH EDITION
CHAPTER 5
THE DATA RESOURCE
2. © 2005 Pearson Prentice-Hall Chapter 5 - 2
Organizations could not function long
without critical business data
Cost to replace data would be very high
Time to reconcile inconsistent data may
be too long
Data often needs to be accessed quickly
WHY MANAGE DATA?
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Data should be:
Cataloged
Named in standard ways
Protected
Accessible to those with a need to know
Maintained with high quality
WHY MANAGE DATA?
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TECHNICAL ASPECTS OF
MANAGING THE DATA RESOURCE
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Data model –
overall map for business data needed to effectively
manage the data
The Data Model
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Data modeling involves:
Methodology, or steps followed to identify
and describe data entities
Notation, or a way to illustrate data entities
graphically
The Data Model
TECHNICAL ASPECTS OF
MANAGING THE DATA RESOURCE
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Entity-relationship diagram (ERD)
Most common method for representing a
data model and organizational data needs
Captures entities and their relationships
Entities – things about which data are
collected
Attributes – actual elements of data that are
to be collected
TECHNICAL ASPECTS OF
MANAGING THE DATA RESOURCE
The Data Model
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Figure 5.1 Entity-Relationship Diagram
NOTE:
• Entities are Customer, Order, and Product.
• Attributes of the Customer entity could be
customer last name, first name, street, city, …
TECHNICAL ASPECTS OF
MANAGING THE DATA RESOURCE
The Data Model
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Enterprise modeling
Top-down approach
Describes organization and data
requirements at high level, independent of
reports, screens, or detailed specifications
Not biased by how business operates today
TECHNICAL ASPECTS OF
MANAGING THE DATA RESOURCE
Data Modeling
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Enterprise Modeling Steps:
Divide work into major
functions
Divide each function into
processes
Divide processes into
activities
List data entities
assigned to each activity
Identify relationships
between entities
TECHNICAL ASPECTS OF
MANAGING THE DATA RESOURCE
Data Modeling
Figure 5.2 Enterprise Decomposition
for Data Modeling
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View integration
Bottom-up approach
Each report, screen, form, document
produced from databases first … each
called a user view
TECHNICAL ASPECTS OF
MANAGING THE DATA RESOURCE
Data Modeling
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View Integration Steps:
Create user views
Identify data elements in each user view and put into a
structure called a normal form
Normalize user views
Integrate set of entities from normalization into one
description
TECHNICAL ASPECTS OF
MANAGING THE DATA RESOURCE
Data Modeling
Normalization –
process of creating simple data structures from more complex
ones
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Data modeling guidelines:
Objective – effort must be justified by need
Scope – broader scope, more chance of
failure
Outcome – uncertainty leads to failure
Timing – consider an evolutionary approach
TECHNICAL ASPECTS OF
MANAGING THE DATA RESOURCE
Data Modeling
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TECHNICAL ASPECTS OF
MANAGING THE DATA RESOURCE
Database Architecture
Database –
shared collection of logically related data, organized to
meet needs of an organization
Database Architecture –
way in which the data are structured and stored in the
database
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Figure 5.3 The Data Pyramid
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TECHNICAL ASPECTS OF
MANAGING THE DATA RESOURCE
Six basic database architectures:
1. Hierarchical (top-down organization)
2. Network (high-volume transaction processing)
3. Relational (data arranged in simple tables)
4. Object-oriented (data and methods encapsulated in object
classes)
5. Object-relational (hybrid of relational and object-
oriented)
6. Multidimensional (used by data warehouses)
Database Architecture
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TECHNICAL ASPECTS OF
MANAGING THE DATA RESOURCE
Tools for Managing Data
Database Management System (DBMS) –
support software used to create, manage, and protect
organizational data
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TECHNICAL ASPECTS OF
MANAGING THE DATA RESOURCE
A DBMS helps manage data by providing
seven functions:
1. Data storage, retrieval, update
2. Backup
3. Recovery
4. Integrity control
5. Security control
6. Concurrency control
7. Transaction control
Tools for Managing Data
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TECHNICAL ASPECTS OF
MANAGING THE DATA RESOURCE
Most popular type of database architecture
is relational
Not all relational systems are identical.
Best effort to date for standardizing
relational databases is SQL
Tools for Managing Data
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TECHNICAL ASPECTS OF
MANAGING THE DATA RESOURCE
Contains:
Definition of each entity,
relationship, and data
element
Display formats
Integrity rules
Security restrictions
Volume and sizes
List of applications that use
the data
Tools for Managing Data
Data Dictionary/Directory (DD/D) –
central encyclopedia of data definitions and usage
information … a database about data
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TECHNICAL ASPECTS OF
MANAGING THE DATA RESOURCE
Database Programming
Query language –
a 4 GL, nonprocedural programming language to obtain
data from a database, often provided by the DBMS
SQL query language example:
SELECT ORDER#, CUSTOMER#, CUSTNAME,
ORDER-DATE FROM CUSTOMER, ORDER
WHERE ORDER-DATE > ’04/12/05’
AND CUSTOMER.CUSTOMER# =
ORDER.CUSTOMER#
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The need to manage data is permanent
Data can exist at several levels
Application software should be separate from the
database
Application software can be classified by how they
treat data
1. Data capture
2. Data transfer
3. Data analysis and presentation
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MANAGING DATA
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Principles in Managing Data
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Application software should be
considered disposable
Data should be captured once
There should be strict data standards
MANAGERIAL ISSUES IN
MANAGING DATA
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Principles in Managing Data
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MANAGERIAL ISSUES IN
MANAGING DATA
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Principles in Managing Data
Figure 5.5 Types of Data Standards
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MANAGERIAL ISSUES IN
MANAGING DATA
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The Data Management Process
Figure 5.6 Asset Management Functions
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Figure 5.7 The Data Warehouse
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MANAGERIAL ISSUES IN
MANAGING DATA
Organizations should have policies regarding:
Data ownership
Data administration
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Data Management Policies
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MANAGING DATA
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Data Ownership
Corporate information policy –
foundation for managing the ownership of data
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Figure 5.8 Example Data Access Policy
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Data Administration
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Key functions of the data administration group:
Promote and control data sharing
Analyze the impact of changes to application systems when data
definitions change
Maintain the data dictionary
Reduce redundant data and processing
Reduce system maintenance costs and improve system
development productivity
Improve quality and security of data
Insure data integrity
MANAGERIAL ISSUES IN
MANAGING DATA
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Data Administration
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Key functions of the database administrator (DBA):
Tuning database management systems.
Selection and evaluation of and training on database technology.
Physical database design.
Design of methods to recover from damage to databases.
Physical placement of databases on specific computers and
storage devices.
The interface of databases with telecommunications and other
technologies.
MANAGERIAL ISSUES IN
MANAGING DATA