ch05 final

31
E. Wainright Martin Carol V. Brown Daniel W. DeHayes Jeffrey A. Hoffer William C. Perkins MANAGING MANAGING INFORMATION INFORMATION TECHNOLOGY TECHNOLOGY FIFTH EDITION CHAPTER 5 THE DATA RESOURCE

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Ch05 Final

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Page 1: Ch05 Final

E. Wainright Martin Carol V. Brown Daniel W. DeHayesJeffrey A. Hoffer William C. Perkins

MANAGINGMANAGINGINFORMATIONINFORMATIONTECHNOLOGYTECHNOLOGY

FIFTH EDITION

CHAPTER 5

THE DATA RESOURCE

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© 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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© 2005 Pearson Prentice-Hall Chapter 5 - 3

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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© 2005 Pearson Prentice-Hall Chapter 5 - 4

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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© 2005 Pearson Prentice-Hall Chapter 5 - 5 Page 135

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 RESOURCEThe Data Model

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© 2005 Pearson Prentice-Hall Chapter 5 - 7 Page 135 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 RESOURCEThe Data Model

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© 2005 Pearson Prentice-Hall Chapter 5 - 8 Page 136

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 RESOURCEData Modeling

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© 2005 Pearson Prentice-Hall Chapter 5 - 9 Page 136

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 RESOURCEData Modeling

Figure 5.2 Enterprise Decomposition for Data Modeling

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© 2005 Pearson Prentice-Hall Chapter 5 - 10 Page 136

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 RESOURCEData 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 RESOURCEData Modeling

Normalization – process of creating simple data structures from more complex ones

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© 2005 Pearson Prentice-Hall Chapter 5 - 12 Page 136-137

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 RESOURCEData Modeling

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© 2005 Pearson Prentice-Hall Chapter 5 - 13 Page 137

TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCEDatabase 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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© 2005 Pearson Prentice-Hall Chapter 5 - 14 Page 137 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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© 2005 Pearson Prentice-Hall Chapter 5 - 16 Page 138

TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCETools for Managing Data

Database Management System (DBMS) – support software used to create, manage, and protect organizational data

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© 2005 Pearson Prentice-Hall Chapter 5 - 17 Page 139

TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE

A DBMS helps manage data by providing seven functions:

1. Data storage, retrieval, update2. Backup3. Recovery4. Integrity control5. Security control6. Concurrency control7. Transaction control

Tools for Managing Data

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© 2005 Pearson Prentice-Hall Chapter 5 - 18 Page 139

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

Important Notes:

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© 2005 Pearson Prentice-Hall Chapter 5 - 19 Page 139-140

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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© 2005 Pearson Prentice-Hall Chapter 5 - 20 Page 140

TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCEDatabase 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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© 2005 Pearson Prentice-Hall Chapter 5 - 21

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 capture2. Data transfer3. Data analysis and presentation

MANAGERIAL ISSUES IN MANAGING DATA

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Principles in Managing Data

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© 2005 Pearson Prentice-Hall Chapter 5 - 22 Page 142 Figure 5.4

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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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© 2005 Pearson Prentice-Hall Chapter 5 - 26 Page 146 Figure 5.7 The Data Warehouse

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MANAGERIAL ISSUES IN MANAGING DATA

Organizations should have policies regarding:Data ownership Data administration

Page 148

Data Management Policies

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MANAGERIAL ISSUES IN MANAGING DATA

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Data Ownership

Corporate information policy – foundation for managing the ownership of data

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© 2005 Pearson Prentice-Hall Chapter 5 - 29 Page 149 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

Page 150-151

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