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Modern Database Management 12th edition [Hardback]

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  • Format: Hardback, 600 pages, height x width x depth: 10x10x10 mm, weight: 1340 g
  • Pub. Date: 11-Jan-2016
  • Publisher: Pearson
  • ISBN-10: 0133544613
  • ISBN-13: 9780133544619
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Modern Database Management 12th editionLarger Image
  • Format: Hardback, 600 pages, height x width x depth: 10x10x10 mm, weight: 1340 g
  • Pub. Date: 11-Jan-2016
  • Publisher: Pearson
  • ISBN-10: 0133544613
  • ISBN-13: 9780133544619
Other books in subject:
Permanent link: https://www.kriso.lv/db/9780133544619.html
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Provide the latest information in database development

Focusing on what leading database practitioners say are the most important aspects to database development, Modern Database Management presents sound pedagogy, and topics that are critical for the practical success of database professionals. The Twelfth Edition further facilitates learning with illustrations that clarify important concepts and new media resources that make some of the more challenging material more engaging. Also included are general updates and expanded material in the areas undergoing rapid change due to improved managerial practices, database design tools and methodologies, and database technology.  


Preface xxv
Part I The Context of Database Management
1(50)
An Overview of Part One
1(1)
Chapter 1 The Database Environment and Development Process
2(49)
Learning Objectives
2(1)
Data Matter!
2(1)
Introduction
3(2)
Basic Concepts and Definitions
5(2)
Data
5(1)
Data Versus Information
5(1)
Metadata
6(1)
Traditional File Processing Systems
7(2)
File Processing Systems at Pine Valley Furniture Company
8(1)
Disadvantages of File Processing Systems
8(1)
Program-Data Dependence
8(1)
Duplication of Data
9(1)
Limited Data Sharing
9(1)
Lengthy Development Times
9(1)
Excessive Program Maintenance
9(1)
The Database Approach
9(6)
Data Models
9(1)
Entities
10(1)
Relationships
11(1)
Relational Databases
11(1)
Database Management Systems
11(1)
Advantages of the Database Approach
11(1)
Program-Data Independence
11(1)
Planned Data Redundancy
12(1)
Improved Data Consistency
12(1)
Improved Data Sharing
12(1)
Increased Productivity of Application Development
13(1)
Enforcement of Standards
13(1)
Improved Data Quality
13(1)
Improved Data Accessibility and Responsiveness
14(1)
Reduced Program Maintenance
14(1)
Improved Decision Support
14(1)
Cautions About Database Benefits
14(1)
Costs and Risks of the Database Approach
14(1)
New, Specialized Personnel
15(1)
Installation and Management Cost and Complexity
15(1)
Conversion Costs
15(1)
Need for Explicit Backup and Recovery
15(1)
Organizational Conflict
15(1)
Components of the Database Environment
15(2)
The Database Development Process
17(7)
Systems Development Life Cycle
18(1)
Planning---Enterprise Modeling
18(1)
Planning---Conceptual Data Modeling
18(1)
Analysis---Conceptual Data Modeling
18(1)
Design---Logical Database Design
19(1)
Design---Physical Database Design and Definition
20(1)
Implementation---Database Implementation
20(1)
Maintenance---Database Maintenance
20(1)
Alternative Information Systems (IS) Development Approaches
21(1)
Three-Schema Architecture for Database Development
22(2)
Managing the People Involved in Database Development
24(1)
Evolution of Database Systems
24(3)
1960s
26(1)
1970s
26(1)
1980s
26(1)
1990s
26(1)
2000 and Beyond
27(1)
The Range of Database Applications
27(4)
Personal Databases
28(1)
Multitier Client/Server Databases
28(1)
Enterprise Applications
29(2)
Developing a Database Application for Pine Valley Furniture Company
31(20)
Database Evolution at Pine Valley Furniture Company
32(1)
Project Planning
33(1)
Analyzing Database Requirements
34(2)
Designing the Database
36(3)
Using the Database
39(1)
Administering the Database
40(1)
Future of Databases at Pine Valley
41(1)
Summary
41(1)
Key Terms
42(1)
Review Questions
42(2)
Problems and Exercises
44(1)
Field Exercises
45(1)
References
46(1)
Further Reading
46(1)
Web Resources
47(1)
Case: Forondo Artist Management Excellence Inc.
48(3)
Part II Database Analysis
51(102)
An Overview of Part Two
51(2)
Chapter 2 Modeling Data in the Organization
53(61)
Learning Objectives
53(1)
Introduction
53(3)
The E-R Model: An Overview
56(3)
Sample E-R Diagram
56(2)
E-R Model Notation
58(1)
Modeling the Rules of the Organization
59(6)
Overview of Business Rules
60(1)
The Business Rules Paradigm
60(1)
Scope of Business Rules
61(1)
Good Business Rules
61(1)
Gathering Business Rules
62(1)
Data Names and Definitions
62(1)
Data Names
62(1)
Data Definitions
63(1)
Good Data Definitions
63(2)
Modeling Entities and Attributes
65(9)
Entities
65(1)
Entity Type Versus Entity Instance
65(1)
Entity Type Versus System Input, Output, or User
65(1)
Strong Versus Weak Entity Types
66(1)
Naming and Defining Entity Types
67(2)
Attributes
69(1)
Required Versus Optional Attributes
69(1)
Simple Versus Composite Attributes
70(1)
Single-Valued Versus Multivalued Attributes
70(1)
Stored Versus Derived Attributes
71(1)
Identifier Attribute
71(1)
Naming and Defining Attributes
72(2)
Modeling Relationships
74(18)
Basic Concepts and Definitions in Relationships
75(1)
Attributes on Relationships
76(1)
Associative Entities
76(2)
Degree of a Relationship
78(1)
Unary Relationship
78(2)
Binary Relationship
80(1)
Ternary Relationship
81(1)
Attributes or Entity?
82(2)
Cardinality Constraints
84(1)
Minimum Cardinality
84(1)
Maximum Cardinality
84(1)
Some Examples of Relationships and Their Cardinalities
85(1)
A Ternary Relationship
86(1)
Modeling Time-Dependent Data
86(3)
Modeling Multiple Relationships Between Entity Types
89(1)
Naming and Defining Relationships
90(2)
E-R Modeling Example: Pine Valley Furniture Company
92(2)
Database Processing at Pine Valley Furniture
94(20)
Showing Product Information
95(1)
Showing Product Line Information
95(1)
Showing Customer Order Status
96(1)
Showing Product Sales
97(1)
Summary
98(1)
Key Terms
99(1)
Review Questions
99(1)
Problems and Exercises
100(10)
Field Exercises
110(1)
References
110(1)
Further Reading
111(1)
Web Resources
111(1)
Case: Forondo Artist Management Excellence Inc.
112(2)
Chapter 3 The Enhanced E-R Model
114(39)
Learning Objectives
114(1)
Introduction
114(1)
Representing Supertypes and Subtypes
115(7)
Basic Concepts and Notation
116(1)
An Example of a Supertype/Subtype Relationship
117(1)
Attribute Inheritance
118(1)
When to Use Supertype/Subtype Relationships
118(1)
Representing Specialization and Generalization
119(1)
Generalization
119(1)
Specialization
120(1)
Combining Specialization and Generalization
121(1)
Specifying Constraints in Supertype/Subtype Relationships
122(6)
Specifying Completeness Constraints
122(1)
Total Specialization Rule
122(1)
Partial Specialization Rule
122(1)
Specifying Disjointness Constraints
123(1)
Disjoint Rule
123(1)
Overlap Rule
123(1)
Defining Subtype Discriminators
124(1)
Disjoint Subtypes
124(1)
Overlapping Subtypes
125(1)
Defining Supertype/Subtype Hierarchies
125(1)
An Example of a Supertype/Subtype Hierarchy
126(1)
Summary of Supertype/Subtype Hierarchies
127(1)
EER Modeling Example: Pine Valley Furniture Company
128(3)
Entity Clustering
131(3)
Packaged Data Models
134(19)
A Revised Data Modeling Process with Packaged Data Models
136(2)
Packaged Data Model Examples
138(5)
Summary
143(1)
Key Terms
144(1)
Review Questions
144(1)
Problems and Exercises
145(3)
Field Exercises
148(1)
References
148(1)
Further Reading
148(1)
Web Resources
149(1)
Case: Forondo Artist Management Excellence Inc.
150(3)
Part III Database Design
153(88)
An Overview of Part Three
153(2)
Chapter 4 Logical Database Design and the Relational Model
155(51)
Learning Objectives
155(1)
Introduction
155(1)
The Relational Data Model
156(4)
Basic Definitions
156(1)
Relational Data Structure
157(1)
Relational Keys
157(1)
Properties of Relations
158(1)
Removing Multivalued Attributes from Tables
158(1)
Sample Database
158(2)
Integrity Constraints
160(5)
Domain Constraints
160(1)
Entity Integrity
160(2)
Referential Integrity
162(1)
Creating Relational Tables
163(1)
Well-Structured Relations
164(1)
Transforming EER Diagrams into Relations
165(13)
Step 1 Map Regular Entities
166(1)
Composite Attributes
166(1)
Multivalued Attributes
167(1)
Step 2 Map Weak Entities
167(2)
When to Create a Surrogate Key
169(1)
Step 3 Map Binary Relationships
169(1)
Map Binary One-to-Many Relationships
169(1)
Map Binary Many-to-Many Relationships
170(1)
Map Binary One-to-One Relationships
170(1)
Step 4 Map Associative Entities
171(1)
Identifier not Assigned
172(1)
Identifier Assigned
172(1)
Step 5 Map Unary Relationships
173(1)
Unary One-to-Many Relationships
173(1)
Unary Many-to-Many Relationships
174(1)
Step 6 Map Ternary (and n-ary) Relationships
175(1)
Step 7 Map Supertype/Subtype Relationships
176(2)
Summary of EER-to-Relational Transformations
178(1)
Introduction to Normalization
178(4)
Steps in Normalization
179(1)
Functional Dependencies and Keys
179(2)
Determinants
181(1)
Candidate Keys
181(1)
Normalization Example: Pine Valley Furniture Company
182(6)
Step 0 Represent the View in Tabular Form
182(1)
Step 1 Convert to First Normal Form
183(1)
Remove Repeating Groups
183(1)
Select the Primary Key
183(1)
Anomalies in 1NF
184(1)
Step 2 Convert to Second Normal Form
185(1)
Step 3 Convert to Third Normal Form
186(1)
Removing Transitive Dependencies
186(1)
Determinants and Normalization
187(1)
Step 4 Further Normalization
187(1)
Merging Relations
188(2)
An Example
188(1)
View Integration Problems
188(1)
Synonyms
189(1)
Homonyms
189(1)
Transitive Dependencies
189(1)
Supertype/Subtype Relationships
190(1)
A Final Step for Defining Relational Keys
190(16)
Summary
192(2)
Key Terms
194(1)
Review Questions
194(1)
Problems and Exercises
195(9)
Field Exercises
204(1)
References
204(1)
Further Reading
204(1)
Web Resources
204(1)
Case: Forondo Artist Management Excellence Inc.
205(1)
Chapter 5 Physical Database Design and Performance
206(35)
Learning Objectives
206(1)
Introduction
206(1)
The Physical Database Design Process
207(3)
Physical Database Design as a Basis for Regulatory Compliance
208(1)
Data Volume and Usage Analysis
209(1)
Designing Fields
210(3)
Choosing Data Types
211(1)
Coding Techniques
212(1)
Handling Missing Data
213(1)
Denormalizing and Partitioning Data
213(6)
Denormalization
213(1)
Opportunities for and Types of Denormalization
214(2)
Denormalize With Caution
216(1)
Partitioning
217(2)
Designing Physical Database Files
219(9)
File Organizations
221(1)
Heap File Organization
221(1)
Sequential File Organizations
221(1)
Indexed File Organizations
221(3)
Hashed File Organizations
224(3)
Clustering Files
227(1)
Designing Controls for Files
227(1)
Using and Selecting Indexes
228(2)
Creating a Unique Key Index
228(1)
Creating a Secondary (Nonunique) Key Index
228(1)
When to Use Indexes
229(1)
Designing a Database for Optimal Query Performance
230(11)
Parallel Query Processing
230(1)
Overriding Automatic Query Optimization
231(1)
Summary
232(1)
Key Terms
233(1)
Review Questions
233(1)
Problems and Exercises
234(3)
Field Exercises
237(1)
References
237(1)
Further Reading
237(1)
Web Resources
238(1)
Case: Forondo Artist Management Excellence Inc.
239(2)
Part IV Implementation
241(176)
An Overview of Part Four
241(2)
Chapter 6 Introduction to SQL
243(46)
Learning Objectives
243(1)
Introduction
243(2)
Origins of the SQL Standard
245(2)
The SQL Environment
247(4)
Defining a Database in SQL
251(6)
Generating SQL Database Definitions
252(1)
Creating Tables
253(2)
Creating Data Integrity Controls
255(1)
Changing Table Definitions
256(1)
Removing Tables
257(1)
Inserting, Updating, and Deleting Data
257(3)
Batch Input
259(1)
Deleting Database Contents
259(1)
Updating Database Contents
259(1)
Internal Schema Definition in RDBMSs
260(1)
Creating Indexes
260(1)
Processing Single Tables
261(28)
Clauses of the Select Statement
262(2)
Using Expressions
264(1)
Using Functions
265(2)
Using Wildcards
267(1)
Using Comparison Operators
267(1)
Using Null Values
268(1)
Using Boolean Operators
268(3)
Using Ranges for Qualification
271(1)
Using Distinct Values
271(2)
Using In and Not In with Lists
273(1)
Sorting Results: The Order By Clause
274(1)
Categorizing Results: The Group By Clause
275(1)
Qualifying Results by Categories: The HAVING Clause
276(1)
Using and Defining Views
277(4)
Materialized Views
281(1)
Summary
281(1)
Key Terms
282(1)
Review Questions
282(1)
Problems and Exercises
283(3)
Field Exercises
286(1)
References
287(1)
Further Reading
287(1)
Web Resources
287(1)
Case: Forondo Artist Management Excellence Inc.
288(1)
Chapter 7 Advanced SQL
289(48)
Learning Objectives
289(1)
Introduction
289(1)
Processing Multiple Tables
290(20)
Equi-join
291(1)
Natural Join
292(1)
Outer Join
293(2)
Sample Join Involving Four Tables
295(2)
Self-Join
297(1)
Subqueries
298(5)
Correlated Subqueries
303(2)
Using Derived Tables
305(1)
Combining Queries
306(2)
Conditional Expressions
308(1)
More Complicated SQL Queries
308(2)
Tips for Developing Queries
310(4)
Guidelines for Better Query Design
312(2)
Ensuring Transaction Integrity
314(1)
Data Dictionary Facilities
315(2)
Recent Enhancements and Extensions to SQL
317(4)
Analytical and OLAP Functions
317(2)
New Data Types
319(1)
New Temporal Features in SQL
319(1)
Other Enhancements
320(1)
Triggers and Routines
321(6)
Triggers
321(2)
Routines and other Programming Extensions
323(2)
Example Routine in Oracle's PL/SQL
325(2)
Embedded SQL and Dynamic SQL
327(10)
Summary
329(1)
Key Terms
330(1)
Review Questions
330(1)
Problems and Exercises
331(3)
Field Exercises
334(1)
References
334(1)
Further Reading
334(1)
Web Resources
335(1)
Case: Forondo Artist Management Excellence Inc.
336(1)
Chapter 8 Database Application Development
337(37)
Learning Objectives
337(1)
Location, Location, Location!
337(1)
Introduction
338(1)
Client/Server Architectures
338(2)
Databases in a Two-Tier Architecture
340(5)
A VB.NET Example
342(2)
A Java Example
344(1)
Three-Tier Architectures
345(2)
Web Application Components
347(2)
Databases in Three-Tier Applications
349(7)
A JSP Web Application
349(4)
A PHP Example
353(2)
An ASP.NET Example
355(1)
Key Considerations in Three-Tier Applications
356(5)
Stored Procedures
356(3)
Transactions
359(1)
Database Connections
359(1)
Key Benefits of Three-Tier Applications
359(1)
Cloud Computing and Three-Tier Applications
360(1)
Extensible Markup Language (XML)
361(13)
Storing XML Documents
363(1)
Retrieving XML Documents
363(3)
Displaying XML Data
366(1)
XML and Web Services
366(3)
Summary
369(1)
Key Terms
370(1)
Review Questions
370(1)
Problems and Exercises
371(1)
Field Exercises
372(1)
References
372(1)
Further Reading
372(1)
Web Resources
372(1)
Case: Forondo Artist Management Excellence Inc.
373(1)
Chapter 9 Data Warehousing
374(43)
Learning Objectives
374(1)
Introduction
374(2)
Basic Concepts of Data Warehousing
376(4)
A Brief History of Data Warehousing
377(1)
The Need for Data Warehousing
377(1)
Need For a Company-Wide View
377(2)
Need to Separate Operational and Informational Systems
379(1)
Data Warehouse Architectures
380(8)
Independent Data Mart Data Warehousing Environment
380(2)
Dependent Data Mart and Operational Data Store Architecture: A Three-Level Approach
382(2)
Logical Data Mart and Real-Time Data Warehouse Architecture
384(3)
Three-Layer Data Architecture
387(1)
Role of the Enterprise Data Model
388(1)
Role of Metadata
388(1)
Some Characteristics of Data Warehouse Data
388(4)
Status Versus Event Data
388(1)
Transient Versus Periodic Data
389(1)
An Example of Transient and Periodic Data
389(1)
Transient Data
389(2)
Periodic Data
391(1)
Other Data Warehouse Changes
391(1)
The Derived Data Layer
392(16)
Characteristics of Derived Data
392(1)
The Star Schema
393(1)
Fact Tables and Dimension Tables
393(1)
Example Star Schema
394(1)
Surrogate Key
395(1)
Grain of the Fact Table
396(1)
Duration of the Database
397(1)
Size of the Fact Table
397(1)
Modeling Date and Time
398(1)
Variations of the Star Schema
399(1)
Multiple Fact Tables
399(1)
Factless Fact Tables
400(1)
Normalizing Dimension Tables
401(1)
Multivalued Dimensions
401(1)
Hierarchies
402(2)
Slowly Changing Dimensions
404(2)
Determining Dimensions and Facts
406(2)
The Future of Data Warehousing: Integration with Big Data and Analytics
408(9)
Speed of Processing
409(1)
Cost of Storing Data
409(1)
Dealing with Unstructured Data
409(1)
Summary
410(1)
Key Terms
410(1)
Review Questions
411(1)
Problems and Exercises
411(4)
Field Exercises
415(1)
References
415(1)
Further Reading
416(1)
Web Resources
416(1)
Part V Advanced Database Topics
417(119)
An Overview of Part Five
417(2)
Chapter 10 Data Quality and Integration
419(26)
Learning Objectives
419(1)
Introduction
419(1)
Data Governance
420(1)
Managing Data Quality
421(7)
Characteristics of Quality Data
422(1)
External Data Sources
423(1)
Redundant Data Storage and Inconsistent Metadata
424(1)
Data Entry Problems
424(1)
Lack of Organizational Commitment
424(1)
Data Quality Improvement
424(1)
Get the Business Buy-In
424(1)
Conduct a Data Quality Audit
425(1)
Establish a Data Stewardship Program
426(1)
Improve Data Capture Processes
426(1)
Apply Modern Data Management Principles and Technology
427(1)
Apply TQM Principles and Practices
427(1)
Summary of Data Quality
427(1)
Master Data Management
428(1)
Data Integration: An Overview
429(2)
General Approaches to Data Integration
429(1)
Data Federation
430(1)
Data Propagation
431(1)
Data Integration for Data Warehousing: The Reconciled Data Layer
431(6)
Characteristics of Data After ETL
431(1)
The ETL Process
432(1)
Mapping and Metadata Management
432(1)
Extract
433(1)
Cleanse
434(2)
Load and Index
436(1)
Data Transformation
437(8)
Data Transformation Functions
438(1)
Record-Level Functions
438(1)
Field-Level Functions
439(2)
Summary
441(1)
Key Terms
441(1)
Review Questions
441(1)
Problems and Exercises
442(1)
Field Exercises
443(1)
References
443(1)
Further Reading
444(1)
Web Resources
444(1)
Chapter 11 Big Data and Analytics
445(40)
Learning Objectives
445(1)
Introduction
445(2)
Big Data
447(2)
NoSQL
449(11)
Classification of NoSQL Database Management Systems
450(1)
Key-Value Stores
450(1)
Document Stores
450(1)
Wide-Column Stores
451(1)
Graph-Oriented Databases
451(1)
NoSQL Examples
452(1)
Redis
452(1)
MongoDB
452(1)
Apache Cassandra
452(1)
Neo4J
452(1)
Impact of NoSQL on Database Professionals
452(1)
Hadoop
453(1)
Components of Hadoop
454(1)
The Hadoop Distributed File System (HDFS)
454(1)
MapReduce
455(1)
Pig
456(1)
Hive
456(1)
HBase
457(1)
Integrated Analytics and Data Science Platforms
457(1)
HP HAVEN
457(1)
Teradata Aster
457(1)
IBM Big Data Platform
457(1)
Putting It All Together: Integrated Data Architecture
458(2)
Analytics
460(16)
Types of Analytics
461(1)
Use of Descriptive Analytics
462(1)
SQL OLAP Querying
463(2)
Online Analytical Processing (OLAP) Tools
465(2)
Data Visualization
467(2)
Business Performance Management and Dashboards
469(1)
Use of Predictive Analytics
470(1)
Data Mining Tools
470(2)
Examples of Predictive Analytics
472(1)
Use of Prescriptive Analytics
473(1)
Data Management Infrastructure for Analytics
474(2)
Impact of Big Data and Analytics
476(9)
Applications of Big Data and Analytics
476(1)
Business
477(1)
E-government and Politics
477(1)
Science and Technology
478(1)
Smart Health and Well-Being
478(1)
Security and Public Safety
478(1)
Implications of Big Data Analytics and Decision Making
478(1)
Personal Privacy vs. Collective Benefits
479(1)
Ownership and Access
479(1)
Quality and Reuse of Data and Algorithms
479(1)
Transparency and Validation
480(1)
Changing Nature of Work
480(1)
Demands for Workforce Capabilities and Education
480(1)
Summary
480(1)
Key Terms
481(1)
Review Questions
481(1)
Problems and Exercises
482(1)
References
483(1)
Further Reading
484(1)
Web Resources
484(1)
Chapter 12 Data and Database Administration
485(51)
Learning Objectives
485(1)
Introduction
485(1)
The Roles of Data and Database Administrators
486(6)
Traditional Data Administration
486(2)
Traditional Database Administration
488(1)
Trends in Database Administration
489(2)
Data Warehouse Administration
491(1)
Summary of Evolving Data Administration Roles
492(1)
The Open Source Movement and Database Management
492(2)
Managing Data Security
494(5)
Threats to Data Security
495(1)
Establishing Client/Server Security
496(1)
Server Security
496(1)
Network Security
496(1)
Application Security Issues in Three-Tier Client/Server Environments
497(1)
Data Privacy
498(1)
Database Software Data Security Features
499(6)
Views
500(1)
Integrity Controls
500(2)
Authorization Rules
502(1)
User-Defined Procedures
503(1)
Encryption
503(1)
Authentication Schemes
504(1)
Passwords
505(1)
Strong Authentication
505(1)
Sarbanes-Oxley (SOX) and Databases
505(2)
IT Change Management
506(1)
Logical Access to Data
506(1)
Personnel Controls
506(1)
Physical Access Controls
507(1)
IT Operations
507(1)
Database Backup and Recovery
507(8)
Basic Recovery Facilities
508(1)
Backup Facilities
508(1)
Journalizing Facilities
508(1)
Checkpoint Facility
509(1)
Recovery Manager
509(1)
Recovery and Restart Procedures
510(1)
Disk Mirroring
510(1)
Restore/Rerun
510(1)
Maintaining Transaction Integrity
510(2)
Backward Recovery
512(1)
Forward Recovery
513(1)
Types of Data base Failure
513(1)
Aborted Transactions
513(1)
Incorrect Data
513(1)
System Failure
514(1)
Database Destruction
514(1)
Disaster Recovery
514(1)
Controlling Concurrent Access
515(6)
The Problem of Lost Updates
515(1)
Serializability
515(1)
Locking Mechanisms
516(1)
Locking Level
516(1)
Types of Locks
517(1)
Deadlock
518(1)
Managing Deadlock
518(1)
Versioning
519(2)
Data Dictionaries and Repositories
521(2)
Data Dictionary
521(1)
Repositories
521(2)
Overview of Tuning the Database for Performance
523(3)
Installation of the DBMS
523(1)
Memory and Storage Space Usage
523(1)
Input/Output (I/O) Contention
524(1)
CPU Usage
524(1)
Application Tuning
525(1)
Data Availability
526(10)
Costs of Downtime
526(1)
Measures to Ensure Availability
526(1)
Hardware Failures
527(1)
Loss or Corruption of Data
527(1)
Human Error
527(1)
Maintenance Downtime
527(1)
Network-Related Problems
527(1)
Summary
528(1)
Key Terms
528(1)
Review Questions
529(1)
Problems and Exercises
530(2)
Field Exercises
532(1)
References
532(1)
Further Reading
533(1)
Web Resources
533(1)
Glossary of Acronyms
534(2)
Glossary of Terms 536(8)
Index 544