Financial Data Engineering: Design and Build Data-Driven Financial Products (Paperback)
            
暫譯: 金融數據工程:設計與構建數據驅動的金融產品
        
        Khraisha, Tamer
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商品描述
Today, investment in financial technology and digital transformation is reshaping the financial landscape and generating many opportunities. Too often, however, engineers and professionals in financial institutions lack a practical view of the concepts, problems, techniques, and technologies necessary to build a modern, reliable, and scalable financial data infrastructure. This is where financial data engineering is needed.
A data engineer who specializes in finance not only has specific data engineering knowledge, but also a good understanding of financial domain-specific problems, approaches, data ecosystem, data providers, data formats, technological constraints, identifiers, entities, regulatory requirements, and governance.
This book offers a comprehensive, practical, domain-driven approach to financial data engineering with real use cases, market practices, and hands-on projects.
You'll learn:
- The data engineering landscape in the financial sector
- Specific problems encountered in financial data engineering
- Structure, players, and particularities of the financial data domain
- Approaches to designing financial data identification and entity systems
- Financial data governance frameworks, concepts, and best practices
- The financial data engineering lifecycle from ingestion to production
- The varieties and main characteristics of financial data workflows
- How to build financial data pipelines using open source and cloud technologies
商品描述(中文翻譯)
今天,對金融科技和數位轉型的投資正在重塑金融環境並產生許多機會。然而,金融機構中的工程師和專業人士往往缺乏對建立現代、可靠且可擴展的金融數據基礎設施所需的概念、問題、技術和技術的實際看法。這就是金融數據工程所需的地方。
專注於金融的數據工程師不僅擁有特定的數據工程知識,還對金融領域特有的問題、方法、數據生態系統、數據提供者、數據格式、技術限制、標識符、實體、法規要求和治理有良好的理解。
本書提供了一個全面、實用、以領域為驅動的金融數據工程方法,並包含真實的使用案例、市場實踐和實作專案。
您將學到:
- 金融領域的數據工程概況
- 在金融數據工程中遇到的特定問題
- 金融數據領域的結構、參與者和特點
- 設計金融數據識別和實體系統的方法
- 金融數據治理框架、概念和最佳實踐
- 從數據攝取到生產的金融數據工程生命周期
- 金融數據工作流程的多樣性和主要特徵
- 如何使用開源和雲技術構建金融數據管道
 
 
     
     
     
     
     
     
     
     
     
     
     
    
 
     
     
     
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