Data mining and warehousing /

Data Mining is the process of analyzing large amount of data in search of previously undiscovered business patterns. Data Warehousing is a relational/multidimensional database that is designed for Query and Analysis rather than Transaction Processing. This book provides a systematic introduction to...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Prabhu, S.
Otros Autores: Venatesan, N.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New Delhi : New Age International, ©2007.
Temas:
Data mining.
Data warehousing.
Data Mining
Exploration de données (Informatique)
Entrepôts de données (Informatique)
COMPUTERS > Database Management > Data Mining.
Data mining
Data warehousing
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Cover13;
  • Copyright
  • Dedication
  • Preface
  • Acknowledgement
  • Contents
  • Chapter 1 Data Mining and Warehousing Concepts
  • 1.1 Introduction13;
  • 1.2 Data Mining Definitions13;
  • 1.3 Data Mining Tools13;
  • 1.4 Applications of Data Mining13;
  • 1.5 Data Warehousing and Characteristics13;
  • 1.6 Data Warehouse Architecture13;
  • Exercise13;
  • Chapter 2 Learning and Types of Knowledge
  • 2.1 Introduction13;
  • 2.2 What is Learning?13;
  • 2.3 Anatomy of Data Mining13;
  • 2.4 Different Types of Knowledge13;
  • Exercise13;
  • Chapter 3 Knowledge Discovery Process
  • 3.1 Introduction13;
  • 3.2 Evaluation of Data Mining13;
  • 3.3 Stages of the Data Mining Process13;
  • 3.4 Data Mining Operations13;
  • 3.5 Architecture of Data Mining13;
  • Exercise13;
  • Chapter 4 Data Mining Techniques
  • 4.1 Introduction13;
  • 4.2 Classification13;
  • 4.3 Neural Networks13;
  • 4.4 Decision Trees13;
  • 4.5 Genetic Algorithm13;
  • 4.6 Clustering13;
  • 4.7 Online Analytic Processing (OLAP)13;
  • 4.8 Association Rules13;
  • 4.9 Emerging Trends in Data Mining13;
  • 4.10 Data Mining Research Projects13;
  • Exercise13;
  • Chapter 5 Real Time Applications and Future Scope
  • 5.1 Applications of Data Mining13;
  • 5.2 Future Scope13;
  • 5.3 Data Mining Products13;
  • Exercise13;
  • Chapter 6 Data Warehouse Evaluation
  • 6.1 The Calculations for Memory Capacity13;
  • 6.2 Data, Information and Knowledge13;
  • 6.3 Fundamental of Database13;
  • 6.4 OLAP And OLAP Server13;
  • 6.5 Data Warehouses, OLTP, OLAP and Data Mining13;
  • Exercise13;
  • Chapter 7 Data Warehouse Design
  • 7.1 Introduction13;
  • 7.2 The Central Data Warehouse13;
  • 7.3 Data Warehousing Objects13;
  • 7.4 Goals of Data Warehouse Architecture13;
  • 7.5 Data Warehouse Users13;
  • 7.6 Design the Relational Database and OLAP Cubes13;
  • 7.7 Data Warehousing Schemas13;
  • Exercise13;
  • Chapter 8 Partitioning in Data Warehouse
  • 8.1 Introduction13;
  • 8.2 Hardware Partitioning13;
  • 8.3 RAID Levels13;
  • 8.4 Software Partitioning Methods13;
  • Exercise13;
  • Chapter 9 Data Mart and Meta Data
  • 9.1 Introduction13;
  • 9.2 Data Mart13;
  • 9.3 Meta Data13;
  • 9.4 Legacy Systems13;
  • Exercise13;
  • Chapter 10 Backup and Recovery of the Data Warehouse
  • 10.1 Introduction13;
  • 10.2 Types of Backup13;
  • 10.3 Backup the Data Warehouse13;
  • 10.4 Data Warehouse Recovery Models13;
  • Exercise13;
  • Chapter 11 Performance Tuning and Future of data Warehouse
  • 11.1 Introduction13;
  • 11.2 Prioritized Tuning Steps13;
  • 11.3 Challenges of the Data Warehouse13;
  • 11.4 Benefits of Data Warehousing13;
  • 11.5 Future of the Data Warehouse13;
  • 11.6 New Architecture of Data Warehouse13;
  • Exercise13;
  • Appendix A Glossary
  • Appendix B Multiple Choice Questions13;
  • Appendix C Questions & Answers13;
  • Appendix D Model Question Papers13;
  • Bibliography
  • Index.

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