Databases and Information Systems IV 1st Edition by Olegas Vasilecas, Johann Eder, Albertas Caplinskas ISBN 9781607502265 160750226X

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Product details:
ISBN 10: 160750226X
ISBN 13: 9781607502265
Author: Olegas Vasilecas, Johann Eder, Albertas Caplinskas

Databases and Information Systems IV 1st Edition Table of contents:

Part I: Advanced Database Models and Architectures

2. Advanced Relational Database Models

   • Extending the Relational Model
   • Temporal, Spatial, and Multimedia Databases
   • Advanced Query Processing and Optimization Techniques
   • Integrity Constraints and Semantic Modeling
   • Case Studies in Relational Database Extensions

3. Object-Oriented Databases

   • Object-Oriented Data Models: Concepts and Approaches
   • Object-Relational Mapping (ORM) Techniques
   • Query Languages for Object-Oriented Databases
   • Implementing Object-Oriented Features in Databases
   • Real-World Applications of Object-Oriented Databases

4. NoSQL Databases

   • Introduction to NoSQL and Its Types: Document, Columnar, Key-Value, and Graph
   • Comparison of NoSQL and Relational Databases
   • Data Modeling in NoSQL Databases
   • Querying and Indexing Techniques for NoSQL
   • Applications of NoSQL in Big Data and Distributed Systems

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Part II: Database Design and Management

5. Database Design Methodologies

   • Entity-Relationship (ER) and Extended ER Models
   • Normalization Techniques and Their Applications
   • Schema Design and Database Refinement
   • Advanced Techniques for Database Modeling and Design
   • Case Studies in Real-World Database Design

6. Data Warehousing and OLAP

   • Data Warehousing Concepts and Architecture
   • Online Analytical Processing (OLAP)
   • Design and Implementation of Data Warehouses
   • Data Warehouse Optimization Techniques
   • Applications of Data Warehousing in Business Intelligence

7. Distributed and Parallel Databases

   • Distributed Database Architectures and Design
   • Query Processing and Optimization in Distributed Systems
   • Data Replication and Consistency Models
   • Fault Tolerance and Reliability in Distributed Databases
   • Case Studies of Distributed Database Systems

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Part III: Information Systems and Data Integration

8. Information Systems and Their Architecture

   • The Role of Information Systems in Modern Enterprises
   • Information System Architecture: Layers and Components
   • Middleware and Integration Technologies for Information Systems
   • Security, Privacy, and Access Control in Information Systems
   • Enterprise Information Systems and Service-Oriented Architectures (SOA)

9. Data Integration and Interoperability

   • Techniques for Data Integration Across Heterogeneous Systems
   • Data Integration in Federated Databases
   • Web Services and APIs for Data Integration
   • Interoperability Standards and Challenges
   • Real-World Examples of Data Integration in Industry

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Part IV: Emerging Trends and Applications

10. Big Data and Cloud Computing

    • The Role of Big Data in Modern Database Systems
    • Architectures for Big Data Storage and Processing
    • Cloud-Based Database Systems and Their Benefits
    • Data Storage and Management in the Cloud
    • Big Data Analytics and Machine Learning Applications

11. Semantic Web and Linked Data

    • Principles of the Semantic Web and Linked Data
    • RDF, OWL, and SPARQL for Semantic Data Representation
    • Knowledge Graphs and Their Applications
    • Integrating Semantic Web Technologies with Traditional Databases
    • Future Directions for the Semantic Web and Data Integration

12. Mobile and Embedded Databases

    • Mobile Database Systems and Their Requirements
    • Data Management in Mobile and Embedded Environments
    • Querying and Synchronization in Mobile Databases
    • Cloud Integration for Mobile and IoT Databases
    • Case Studies of Mobile Database Applications

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Conclusion
13. Conclusion and Future Trends in Databases and Information Systems
– The Future of Databases: Trends and Innovations
– Next-Generation Data Management Systems
– Challenges in Handling Distributed, Big, and Complex Data
– The Convergence of Databases, AI, and Machine Learning
– Concluding Remarks

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