Requirements: .ePUB reader, 11.4 MB
Overview: 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 and comprehensive understanding 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 developing a data infrastructure for a financial product possesses not only technical data engineering skills but also a solid understanding of financial domain-specific challenges, methodologies, data ecosystems, providers, formats, technological constraints, identifiers, entities, standards, regulatory requirements, and governance. This book offers a comprehensive, practical, domain-driven approach to financial data engineering, featuring real-world use cases, industry practices, and hands-on projects. This book serves a wide audience. This includes individuals working at institutions such as banks, investment firms, financial data providers, asset management companies, security exchanges, regulatory bodies, financial software vendors, and many more. It is designed for data engineers, software developers, quantitative developers, financial analysts, and Machine Learning practitioners who are managing and/or working with financial data and financial data-driven products. Prerequisites: – Python programming; – SQL and PostgreSQL; – Using tools like Python JupyterLab, Python Notebooks, and Pandas; – Running Docker containers locally; – Basic Git commands.
Genre: Non-Fiction > Tech & Devices
Download Instructions:
https://ouo.io/18ssLfq
https://ouo.io/1NpexD7.
