Database Systems Design Implementation and Management 1st edition by Carlos Coronel, Steven Morris, Peter Rob ISBN 0538469684 978-0538469685

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ISBN 10: 0538469684
ISBN 13: 978-0538469685
Author: Carlos Coronel, Steven Morris, Peter Rob

DATABASE SYSTEMS: DESIGN, IMPLEMENTATION, AND MANAGEMENT, NINTH EDITION, a market-leader for database texts, gives readers a solid foundation in practical database design and implementation. The book provides in-depth coverage of database design, demonstrating that the key to successful database implementation is in proper design of databases to fit within a larger strategic view of the data environment. -Updated coverage of data models. -Improved coverage of normalization with a data modeling checklist. -Enhanced coverage of of database design and life cycle. -New review questions, problem sets, and cases throughout the book. With a strong hands-on component that includes real-world examples and exercises, this book will help students develop database design skills that have valuable and meaningful application in the real world

Database Systems: Design, Implementation, and Management 1st Table of contents:

Part I: Introduction to Databases

Chapter 1: Introduction to Database Systems
1.1. What is a Database?
1.2. Database Management Systems (DBMS)
1.3. Types of Databases
1.4. The Role of Databases in Modern Computing
1.5. DBMS Architecture
1.6. Components of a DBMS
1.7. Advantages of Using Databases
1.8. Overview of the Relational Model

Chapter 2: Database System Design
2.1. The Database Development Process
2.2. Requirements Analysis and Conceptual Design
2.3. The Entity-Relationship (ER) Model
2.4. Mapping ER Models to Relational Schemas
2.5. Normalization and Denormalization
2.6. Logical Design of Databases
2.7. Physical Design Considerations

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Part II: Data Models and Query Languages

Chapter 3: The Relational Model
3.1. Basic Concepts of the Relational Model
3.2. Relations, Tuples, and Attributes
3.3. Relational Keys: Primary, Foreign, and Candidate Keys
3.4. Integrity Constraints
3.5. Relational Algebra and Calculus
3.6. Relational Query Languages

Chapter 4: Structured Query Language (SQL)
4.1. Introduction to SQL
4.2. Basic SQL Syntax
4.3. SQL Data Types
4.4. Data Definition Language (DDL)
4.5. Data Manipulation Language (DML)
4.6. Queries in SQL: SELECT, INSERT, UPDATE, DELETE
4.7. Aggregate Functions and Grouping
4.8. SQL Joins
4.9. Subqueries in SQL
4.10. SQL Views and Indexes

Chapter 5: Advanced SQL
5.1. SQL for Set Operations
5.2. Nested Queries and Correlated Subqueries
5.3. Triggers and Stored Procedures
5.4. SQL for Transactions and Concurrency Control
5.5. Error Handling in SQL
5.6. Recursive Queries and Common Table Expressions (CTEs)
5.7. SQL for Managing Complex Data Types

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Part III: Database Design and Normalization

Chapter 6: Relational Database Design
6.1. Functional Dependencies
6.2. Normal Forms: 1NF, 2NF, 3NF, and BCNF
6.3. Multivalued Dependencies and 4NF
6.4. Join Dependencies and 5NF
6.5. Denormalization and its Trade-offs
6.6. Database Design Case Studies

Chapter 7: Indexing and Hashing
7.1. Introduction to Indexing
7.2. Types of Indexes: Single-Level, Multi-Level, and B-Tree Indexes
7.3. Hashing Techniques: Static and Dynamic Hashing
7.4. Index Maintenance and Optimization
7.5. Choosing the Right Indexing Strategy
7.6. Full-Text Indexing

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Part IV: Transaction Management and Concurrency Control

Chapter 8: Transaction Management
8.1. Introduction to Transactions
8.2. ACID Properties
8.3. Transaction States and Lifecycle
8.4. Transaction Logs and Recovery
8.5. Transaction Isolation Levels
8.6. Deadlocks and Their Prevention
8.7. Distributed Transactions

Chapter 9: Concurrency Control
9.1. Introduction to Concurrency Control
9.2. Locking Mechanisms: Pessimistic vs. Optimistic Locking
9.3. Two-Phase Locking Protocol
9.4. Timestamp-Based Protocols
9.5. Multi-Version Concurrency Control (MVCC)
9.6. Distributed Concurrency Control
9.7. Performance Implications of Concurrency Control

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Part V: Advanced Database Topics

Chapter 10: Distributed Databases
10.1. Introduction to Distributed Databases
10.2. Data Distribution and Replication
10.3. Query Processing in Distributed Databases
10.4. Distributed Transactions and Concurrency Control
10.5. Distributed Database Design
10.6. CAP Theorem and Database Consistency Models

Chapter 11: Data Warehousing and Data Mining
11.1. Data Warehousing Concepts
11.2. ETL Process and Data Integration
11.3. OLAP and Data Cubes
11.4. Introduction to Data Mining
11.5. Classification, Clustering, and Association Rules
11.6. Tools and Techniques for Data Mining

Chapter 12: NoSQL Databases
12.1. Introduction to NoSQL Databases
12.2. Key-Value Stores
12.3. Document Stores
12.4. Column-Family Stores
12.5. Graph Databases
12.6. Consistency, Availability, and Partition Tolerance in NoSQL
12.7. Comparing SQL and NoSQL Databases

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Part VI: Database Administration

Chapter 13: Database Security and Authorization
13.1. Database Security Challenges
13.2. Authentication and Authorization Models
13.3. Encryption in Databases
13.4. Auditing and Access Control
13.5. Database Security Policies

Chapter 14: Database Backup and Recovery
14.1. Introduction to Backup Strategies
14.2. Types of Backups: Full, Incremental, Differential
14.3. Backup Scheduling and Automation
14.4. Database Recovery Techniques
14.5. Point-in-Time Recovery
14.6. High Availability and Disaster Recovery Solutions

Chapter 15: Database Administration
15.1. Roles and Responsibilities of a Database Administrator
15.2. Database Performance Tuning
15.3. Query Optimization
15.4. Database Monitoring and Maintenance
15.5. Database Migration and Upgrades
15.6. Database Documentation and Best Practices

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Part VII: Emerging Trends in Databases

Chapter 16: Cloud Databases
16.1. Introduction to Cloud Computing
16.2. Cloud Database Models
16.3. Benefits and Challenges of Cloud Databases
16.4. Cloud Database Deployment Strategies
16.5. Managing Data in the Cloud

Chapter 17: Big Data and NoSQL Systems
17.1. Introduction to Big Data
17.2. Characteristics of Big Data
17.3. Big Data Technologies: Hadoop and Spark
17.4. Big Data Storage and Processing
17.5. NoSQL Databases in Big Data Applications
17.6. Data Lakes vs. Data Warehouses

Chapter 18: Future Trends in Database Systems
18.1. Artificial Intelligence in Database Management
18.2. Machine Learning for Database Optimization
18.3. Blockchain and Distributed Ledgers
18.4. Quantum Computing and Databases
18.5. Emerging Database Architectures

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Appendices

A. SQL Syntax Summary
B. Normalization Summary
C. Database System Software and Tools
D. Additional Resources for Learning Databases
E. Index

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