Yonghong BI Financial Industry Solutions

Facing the challenges of big data, Yonghong BI financial industry solutions: At the strategic level, financial enterprises should establish a "data-driven" development model, improve the data operation system, and implement a big data operation center. At the tactical level, the core value and competitiveness of finance will be comprehensively enhanced through applications such as operation optimization, management improvement, and risk control.

The urgent task of building a bank's big data operation center should focus on the three major construction goals of operation optimization, management improvement, and risk control, which are mainly reflected in:
1. Operation optimization with user data as the core, through customer profiling, precision marketing, product optimization, and public opinion analysis , market and channel analysis to comprehensively improve operational efficiency.
2. Management improvement oriented by input-output and value contribution, and truly achieve refined management through applications such as performance appraisal, leadership cockpit, and management accounting platform.
3. Use multi-dimensional security judgment and more fine-grained modeling and prediction to realize SME loan assessment, real-time fraud transaction analysis, anti-money laundering business analysis and other applications to strengthen the identification, evaluation and prediction of commercial bank risks, and effectively prevent Financial risk.
Yonghong BI financial industry solutions are divided into the following layers from data source to final presentation:
·ETL layer: PC server is used as ETL front-end to clean, convert and load data.
·Offline analytical computing platform: Hadoop distributed storage is adopted. Supports structured and unstructured data storage and facilitates scale-out when the amount of data increases. The data in the storage layer can be processed. According to the analysis needs, it can perform data model calculation, mining analysis and other large-scale batch computing tasks with low timeliness.
·Real-time online analysis platform: Yonghong high-performance MPP data mart is used as the medium. MPP distributed data marts support high concurrency and high availability. Each data mart is the detailed data of light-weight modeling based on a topic. The data is distributed and stored on each node and backed up at the same time. . Data is efficiently compressed, tagged, and stored on disk in a column-stored manner. When query calculation is required, memory calculation is used for data calculation, and each machine node will calculate at the same time, and finally the result will be sent to the application layer for display.
·Application layer: Use Yonghong Agile BI to provide self-service analysis tools to visualize and display data in offline and online analysis platforms. Both end users and IT developers can access the BI system through mainstream browsers, and users can also access the system through mobile terminals. The BI system provides functions such as system monitoring, multi-level management of authority, multi-dimensional data analysis, etc. It also supports self-service report design and data analysis.