Application Challenges and Breakthrough Strategies of Financial Big Data Analysis Tools in Financial Practice Teaching

Abstract

In the context of deep digital economy integration, financial work has transitioned from traditional accounting to intelligent analysis,
making financial big data analysis tools essential competencies for professionals. Their application in practice teaching is critical to bridge the
gap between theory and job requirements.Among these tools, Python has emerged as a powerful and versatile solution for financial big data
analysis, with its application proficiency becoming a critical benchmark for enterprises in selecting financial talent. This study deeply analyzes
the core challenges in terms of teachers, courses, tool adaptability, and practical scenarios during the application process of financial big data
analysis tools (with a focus on the use of Python) based on the current situation of financial practice teaching, and aligns with the financial
professional talent cultivation objectives to propose targeted breakthrough strategies, aiming to optimize teaching models, enhance students
data processing and financial decision support capabilities, address the challenge that teaching is disconnected from job requirements, and
provide actionable ideas for the reform in financial practice teaching.