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Full Description
Data Architecture: From Zen to Reality explains the principles underlying data architecture, how data evolves with organizations, and the challenges organizations face in structuring and managing their data. Using a holistic approach to the field of data architecture, the book describes proven methods and technologies to solve the complex issues dealing with data. It covers the various applied areas of data, including data modelling and data model management, data quality, data governance, enterprise information management, database design, data warehousing, and warehouse design. This text is a core resource for anyone customizing or aligning data management systems, taking the Zen-like idea of data architecture to an attainable reality.
The book presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios. It teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions. It includes the detail needed to illustrate how the fundamental principles are used in current business practice. The book is divided into five sections, one of which addresses the software-application development process, defining tools, techniques, and methods that ensure repeatable results.
Data Architecture is intended for people in business management involved with corporate data issues and information technology decisions, ranging from data architects to IT consultants, IT auditors, and data administrators. It is also an ideal reference tool for those in a higher-level education process involved in data or information technology management.
Contents
Section One: The Principles1: Understanding Architectural Principles2: Enterprise Architecture Frameworks and Methodologies3. Enterprise Level Data Architecture Practices4: Understanding Development Methodologies
Section Two: The Problem5: Business Evolution6 Business Organizations7. Productivity inside the Data Organization8. Solutions That Cause Problems
Section Three: The Process9. Data Organization Practices10. Models and Model Repositories11. Model Constructs and Model Types12. Time as a Dimension of the Database13. Concepts of Clustering, Indexing and Structures
Section Four: The Product14. Basic Requirements for Physical Design15. Physical Database Considerations16. Interpretation of Models
Section Five: Specialized Databases17. Data Warehouses I18. Data Warehouses II19. Dimensional Warehouses from Enterprise Models20. The Enterprise Data Warehouse21. Object and Object/Relational Databases22. Distributed Databases
