Principles of Database Management

Principles of Database Management

Book Description
This comprehensive textbook teaches the fundamentals of database design, modeling, systems, data storage, and the evolving world of data warehousing, governance and more. Written by experienced educators and experts in big data, analytics, data quality, and data integration, it provides an up to date approach to database management. This full color, illustrated text has a balanced theory practice focus, covering essential topics, from established database technologies to recent trends, like Big Data, NoSQL, and more. Fundamental concepts are supported by real world examples, query and code walkthroughs, and figures, making it perfect for introductory courses for advanced undergraduates and graduate students in information systems or computer science. These examples are further supported by an online playground with multiple learning environments, including MySQL, MongoDB, Neo4j Cypher, and tree structure visualization. This combined learning approach connects key concepts throughout the text to the important, practical tools to get started in database management.


Part I - Databases and Database Design
1. Fundamental Concepts of Database Management
2. Architecture and Categorization of DBMSs
3. Conceptual Data Modeling Using the (E)ER Model and UML Class Diagram
4. Organizational Aspects of Data Management

Part II - Types of Database Systems
5. Legacy Databases
6. Relational Databases: The Relational Model
7. Relational Databases: Structured Query Language (SQL)
8. Object-Oriented Databases and Object Persistence
9. Extended Relational Databases
10. XML Databases
11. NoSQL Databases

Part III- Physical Data Storage, Transaction Management, and Database Access
12. Physical File Organization and Indexing
13. Physical Database Organization
14. Basics of Transaction Management
15. Accessing Databases and Database APIs
16. Data Distribution and Distributed Transaction Management

Part IV - Data Warehousing, Data Governance, and (Big) Data Analytics
17. Data Warehousing and Business Intelligence
18. Data Integration, Data Quality, and Data Governance
19. Big Data
20. Analytics

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