Star Schema The Complete Reference (Paperback)
暫譯: 星型架構完全參考手冊 (平裝本)
Christopher Adamson
- 出版商: McGraw-Hill Education
- 出版日期: 2010-04-02
- 售價: $1,750
- 貴賓價: 9.5 折 $1,663
- 語言: 英文
- 頁數: 510
- 裝訂: Paperback
- ISBN: 0071744320
- ISBN-13: 9780071744324
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相關分類:
資料庫、Data Science
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商品描述
The definitive guide to dimensional design for your data warehouse
Learn the best practices of dimensional design. Star Schema: The Complete Reference offers in-depth coverage of design principles and their underlying rationales. Organized around design concepts and illustrated with detailed examples, this is a step-by-step guidebook for beginners and a comprehensive resource for experts.
This all-inclusive volume begins with dimensional design fundamentals and shows how they fit into diverse data warehouse architectures, including those of W.H. Inmon and Ralph Kimball. The book progresses through a series of advanced techniques that help you address real-world complexity, maximize performance, and adapt to the requirements of BI and ETL software products. You are furnished with design tasks and deliverables that can be incorporated into any project, regardless of architecture or methodology.
- Master the fundamentals of star schema design and slow change processing
- Identify situations that call for multiple stars or cubes
- Ensure compatibility across subject areas as your data warehouse grows
- Accommodate repeating attributes, recursive hierarchies, and poor data quality
- Support conflicting requirements for historic data
- Handle variation within a business process and correlation of disparate activities
- Boost performance using derived schemas and aggregates
- Learn when it's appropriate to adjust designs for BI and ETL tools
商品描述(中文翻譯)
《數據倉儲維度設計的權威指南》
學習維度設計的最佳實踐。《星型架構:完整參考》深入探討設計原則及其背後的理論。這本書圍繞設計概念組織,並以詳細範例進行說明,是初學者的逐步指南,也是專家的全面資源。
這本全方位的書籍從維度設計的基本原則開始,展示它們如何融入各種數據倉儲架構,包括 W.H. Inmon 和 Ralph Kimball 的架構。書中逐步介紹一系列先進技術,幫助您應對現實世界的複雜性,最大化性能,並適應 BI 和 ETL 軟體產品的需求。您將獲得可納入任何專案的設計任務和交付物,無論架構或方法論如何。
- 精通星型架構設計和緩慢變更處理的基本原則
- 確定需要多個星型或立方體的情況
- 隨著數據倉儲的增長,確保各主題領域之間的相容性
- 適應重複屬性、遞歸層級和不良數據質量
- 支持歷史數據的衝突需求
- 處理業務流程中的變異和不同活動之間的關聯
- 使用衍生架構和聚合來提升性能
- 學習何時適合調整 BI 和 ETL 工具的設計