Download - Ch05 Final
E. Wainright Martin Carol V. Brown Daniel W. DeHayesJeffrey A. Hoffer William C. Perkins
MANAGINGMANAGINGINFORMATIONINFORMATIONTECHNOLOGYTECHNOLOGY
FIFTH EDITION
CHAPTER 5
THE DATA RESOURCE
© 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?
Page 135
© 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?
Page 135
© 2005 Pearson Prentice-Hall Chapter 5 - 4
TECHNICAL ASPECTS OF MANAGING THE DATA RESOURCE
Page 135
Data model – overall map for business data needed to effectively manage the data
The Data Model
© 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
© 2005 Pearson Prentice-Hall Chapter 5 - 6 Page 135
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
© 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
© 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
© 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
© 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
© 2005 Pearson Prentice-Hall Chapter 5 - 11 Page 136
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
© 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
© 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
© 2005 Pearson Prentice-Hall Chapter 5 - 14 Page 137 Figure 5.3 The Data Pyramid
© 2005 Pearson Prentice-Hall Chapter 5 - 15 Page 138
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
© 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
© 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
© 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:
© 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
© 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#
© 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
Page 140
Principles in Managing Data
© 2005 Pearson Prentice-Hall Chapter 5 - 22 Page 142 Figure 5.4
© 2005 Pearson Prentice-Hall Chapter 5 - 23
Application software should be considered disposable
Data should be captured once There should be strict data standards
MANAGERIAL ISSUES IN MANAGING DATA
Page 143
Principles in Managing Data
© 2005 Pearson Prentice-Hall Chapter 5 - 24
MANAGERIAL ISSUES IN MANAGING DATA
Page 143
Principles in Managing Data
Figure 5.5 Types of Data Standards
© 2005 Pearson Prentice-Hall Chapter 5 - 25
MANAGERIAL ISSUES IN MANAGING DATA
Page 144
The Data Management Process
Figure 5.6 Asset Management Functions
© 2005 Pearson Prentice-Hall Chapter 5 - 26 Page 146 Figure 5.7 The Data Warehouse
© 2005 Pearson Prentice-Hall Chapter 5 - 27
MANAGERIAL ISSUES IN MANAGING DATA
Organizations should have policies regarding:Data ownership Data administration
Page 148
Data Management Policies
© 2005 Pearson Prentice-Hall Chapter 5 - 28
MANAGERIAL ISSUES IN MANAGING DATA
Page 148
Data Ownership
Corporate information policy – foundation for managing the ownership of data
© 2005 Pearson Prentice-Hall Chapter 5 - 29 Page 149 Figure 5.8 Example Data Access Policy
© 2005 Pearson Prentice-Hall Chapter 5 - 30
Data Administration
Page 150
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
© 2005 Pearson Prentice-Hall Chapter 5 - 31
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