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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