·Integrated analysis identifies the public’s genuine needs and enhances the application of data forecasting to help the government implement service and management measures that are more people-oriented, convenient, targeted, and effective.
·Take population analysis as an example: Collect basic population data—including regional birth rates, age distribution, and gender distribution—to accurately assess future regional needs for public infrastructure in areas such as education, healthcare, public health, and culture, thereby providing a scientific basis for formulating supporting policies for public service management.

Leveraging the SDC ETL product’s robust capabilities for integrating diverse, heterogeneous data from multiple sources, the project has aggregated and integrated dozens of data categories, covering information such as airport flights, flight routes, gate assignments, passengers, and baggage. By utilizing these efficient data integration capabilities, the project has resolved issues such as the fragmentation of underlying data in user information systems, the inability to merge real-time data, and obstacles to accessing critical data.

· Real-time Capital Flows: Track capital flows in key regions, key industries, frequent and similar-amount transactions, seasonal flows, holiday-related flows, and occasional large-scale capital movements.
· Data-Driven Credit Risk Management: By integrating big data sources (including P2P platforms, microfinance institutions, credit bureaus, banks, third-party payment providers, and internet big data), connecting diverse application scenarios, and collecting data from online and business platforms in the virtual economy, the system provides decentralized, distributed querying capabilities. This approach addresses the current industry-wide issue of information silos that lead to data gaps, enabling efficient risk management.