Data Architecture : A Primer for the Data Scientist, 2/e

Data Architecture: A Primer for the Data Scientist: Big Data, Data Warehouse and Data Vault, Second Edition, addresses how Big Data fits within the existing information infrastructure and data warehousing systems. This is an essential topic as researchers and engineers increasingly need to deal with large and complex sets of data. Until data is gathered and placed into an existing framework or architecture, it cannot be used to its full potential. Drawing upon years of practical experience and using numerous examples and case studies from across industries, the authors explain where Big Data fits, giving data scientists the necessary context for how pieces of the puzzle should fit together.

• Reviews the exponential growth of Big Data integration and applications across industries - from healthcare to finance
• Places new emphasis on end state architecture as a lens for understanding the architecture of Big Data
• Explains how Big Data fits within an existing systems environment, as well as the value of data transformation and redundancy
• Includes new chapters on data lakes, ponds, landing zones, IoT, edge computing, data modeling and taxonomies

《資料架構：資料科學家入門指南：大數據、資料倉儲和資料庫，第二版》探討了大數據如何融入現有的資訊基礎設施和資料倉儲系統。這是一個重要的主題，因為研究人員和工程師越來越需要處理大型和複雜的資料集。在將資料收集並放入現有的框架或架構之前，它無法充分發揮其潛力。作者們根據多年的實踐經驗，並使用來自各行各業的眾多例子和案例研究，解釋了大數據的位置，為資料科學家提供了必要的上下文，以了解如何將這些拼圖的各個部分組合在一起。

- 回顧了大數據在各行各業中整合和應用的指數級增長，從醫療保健到金融。
- 將對最終架構的重點放在了理解大數據架構的角度上。
- 解釋了大數據如何融入現有的系統環境，以及數據轉換和冗余的價值。
- 新增了關於數據湖、池塘、登陸區、物聯網、邊緣計算、數據建模和分類的章節。