Includes bibliographical references and index.

Vendor-supplied metadata.

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.

Annotation This resource provides a complete introduction to data warehousing, applications and the business context so readers can get-up and running fast. It explains theoretical concepts and provides hands-on instruction on how to build and implement a data warehouse. In addition to demystifying data vault modelling with beginning, intermediate and advanced techniques, it discusses the advantages of the data vault approach over other techniques, as well as the latest updates to data vault 2.0 and multiple improvements to data vault 1.0.