Building a scalable data warehouse with data vault 2.0 /

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Linstedt, Daniel (Autor), Olschimke, Michael (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam : Morgan Kaufmann is an imprint of Elsevier, 2015.
Temas:
Data warehousing.
Entrep�ots de donn�ees (Informatique)
BUSINESS & ECONOMICS > Industrial Management.
BUSINESS & ECONOMICS > Management.
BUSINESS & ECONOMICS > Management Science.
BUSINESS & ECONOMICS > Organizational Behavior.
Data warehousing
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Cover; Title Page; Copyright Page; Contents; Authors Biography; Daniel Linstedt; Michael Olschimke; Foreword; Preface; Acknowledgments; Daniel Linstedt; Michael Olschimke; Chapter 1
  • Introduction to Data Warehousing; 1.1
  • History of Data Warehousing; 1.1.1
  • Decision Support Systems; 1.1.2
  • Data Warehouse Systems; 1.2
  • The Enterprise Data Warehouse Environment; 1.2.1
  • Access; 1.2.2
  • Multiple Subject Areas; 1.2.3
  • Single Version of Truth; 1.2.4
  • Single Version of Facts; 1.2.5
  • Mission Criticality; 1.2.6
  • Scalability; 1.2.7
  • Big Data; 1.2.8
  • Performance Issues; 1.2.9
  • Complexity.
  • 1.2.10
  • Auditing and Compliance1.2.11
  • Costs; 1.2.12
  • Other Business Requirements; 1.3
  • Introduction to Data Vault 2.0; 1.4
  • Data Warehouse Architecture; 1.4.1
  • Typical Two-Layer Architecture; 1.4.2
  • Typical Three-Layer Architecture; References; Chapter 2
  • Scalable Data Warehouse Architecture; 2.1
  • Dimensions of Scalable Data Warehouse Architectures; 2.1.1
  • Workload; 2.1.2
  • Data Complexity; 2.1.3
  • Analytical Complexity; 2.1.4
  • Query Complexity; 2.1.5
  • Availability; 2.1.6
  • Security; 2.2
  • Data Vault 2.0 Architecture; 2.2.1
  • Business Rules Definition.
  • 2.2.2
  • Business Rules Application2.2.3
  • Staging Area Layer; 2.2.4
  • Data Warehouse Layer; 2.2.5
  • Information Mart Layer; 2.2.6
  • Metrics Vault; 2.2.7
  • Business Vault; 2.2.8
  • Operational Vault; 2.2.9
  • Managed Self-Service BI; 2.2.10
  • Other Features; References; Chapter 3
  • The Data Vault 2.0 Methodology; 3.1
  • Project Planning; 3.1.1
  • Capability Maturity Model Integration; 3.1.1.1
  • Capability Levels; 3.1.1.2
  • Maturity Levels; 3.1.1.3
  • Advancing to Maturity Level 5; 3.1.1.4
  • Integrating CMMI in the Data Vault 2.0 Methodology; 3.1.2
  • Managing the Project; 3.1.2.1
  • Scrum.
  • 3.1.2.2
  • Iterative Approach3.1.2.3
  • Product and Sprint Backlog; 3.1.2.4
  • Integrating Scrum with the Data Vault 2.0 Methodology; 3.1.3
  • Defining the Project; 3.1.3.1
  • Agile Requirements Gathering; 3.1.4
  • Estimation of the Project; 3.1.4.1
  • Function Point Analysis; 3.1.4.2
  • Measuring with Function Points; 3.1.4.3
  • Function Point Analysis for Data Warehousing; 3.1.4.4
  • Boundaries in Data Warehousing; 3.1.4.5
  • Estimating Size; 3.1.4.6
  • Assessing ETL Complexity Factors; 3.1.4.7
  • Applying Function Point Analysis to Data Warehousing.
  • 3.1.4.8
  • Function Points for Enterprise Data Warehouse3.2
  • Project Execution; 3.2.1
  • Traditional Software Development Life-Cycle; 3.2.1.1
  • Requirements Engineering; 3.2.1.2
  • Design; 3.2.1.3
  • Implementation and Unit Testing; 3.2.1.4
  • Integration and System Testing; 3.2.1.5
  • Operation and Maintenance; 3.2.2
  • Applying Software Development Life-Cycle to the Data Vault 2.0 Methodology; 3.2.3
  • Parallel Teams; 3.2.4
  • Technical Numbering; 3.3
  • Review and Improvement; 3.3.1
  • Six Sigma; 3.3.1.1
  • Applying Six Sigma to Software; 3.3.1.2
  • Six Sigma Framework; 3.3.1.3
  • DMAIC Improvement.
  • 3.3.1.4
  • Applying Six Sigma to Data Warehousing.

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