After years of accumulation, the credit card center has formed a complete customer analysis and machine learning modeling system. However, with the introduction of external data and business diversification, business departments' needs for data analysis and mining are increasing, and timeliness requirements are getting higher. Traditional analysis tools, due to problems such as incomplete data volume and single-machine multi-tenancy, gradually cannot meet the needs of business departments to analyze and model customers.

The value of massive data in the financial industry—how to operate more precisely, manage more effectively, and monitor more comprehensively—makes building a full financial operation panorama increasingly important. The China Foreign Exchange Trade System (CFETS) big data visualization project provides visualization support for the foreign exchange trade center through a big data visualization software system, realizing big data aggregation, data analysis, and data visualization of foreign exchange trading business.

Shenzhen Baosheng Village Bank mainly serves technology enterprises in the Shenzhen area. In daily operations, it often needs to closely track and view various key operating indicators and analyze related business data. However, limited by the scale of its technology team and R&D strength, in the past it could only submit business requirements and then have an outsourcing team implement them through customized reports. With continuous business development and increasing business diversification, the drawbacks of the existing data management method—long development cycles, untimely responses, and inflexible requirement changes—have become increasingly obvious, making it harder to meet and support business needs.