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Data Support
Data Control
Refinement & Integration
Data Analysis
In order to solve the problem of chimney data construction, the enterprise-level data platform is a common method for companies to refine and integrate gold data (accounting, transactions, customers, etc.). It is in line with standard software engineering specifications that data warehouses are important for digital transformation. Support is to create a good basic data platform for bank business process improvement, cost control, quality control, etc.
It is the basic data platform for all bank management applications and the data support platform for data retrieval, query and decision-making by the banking business department. Relying on the powerful technical architecture of the data warehouse and the powerful performance of professional data warehouse software, it can complete the sorting, storage, export, query and analysis requirements of various bank business data. It is a very stable OLAP data platform system
Platform Function
A unified internal and external data exchange collection platform realizes data collection functions of various relational databases, various mainstream file imports, and direct connection to third-party system interfaces, and can usually achieve data batch collection and real-time data collection
According to the FS-LDM financial data model, a consistent dimensional model is adopted, and a unified, consistent, expansive, analytical and decision-oriented data set is formed through the integration and integrated ETL processing of various messy data
Support traditional database, MPP database and big data platform for long-term continuous storage of collected original data and integrated data, which is convenient for historical data management and application
Provide data distribution to branches or other application systems in accordance with the agreed format and mode. The distributed data format can be a text file or a message interface
Achieve a one-stop unified login to the data application portal, so that business personnel can obtain the data they care about through simple operations. The data platform will provide historical data queries, reports, indicator libraries, management driving layer and other conventional applications
Through the metadata management component, you can clarify what the data is and how to better use it; through the data quality component, you can check data problems and correct the problematic data in time, so that the data analysis results are more accurate and the correct analysis results can be provided for business use
Platform Advantage
Use ETL tools, visual scheduling tools, BI suites, presentation portals and other platform tools with independent intellectual property rights to ensure the project is efficient, high-quality, and low-cost
Based on the construction of various types of bank data warehouse systems for many years, it has accumulated logical data models for various business areas of the bank, which is extremely scalable and forward-looking, and is suitable for the business data requirements of various bank management application systems
Including on the basis of summarizing various banking businesses, compiling and providing a complete set of bank management indicators system to complete the generation, storage and display of various macro statistical information of the bank
Through a variety of technical means, such as clustering, caching technology, column storage technology, etc., to ensure that the data processing query display is efficient, and can cope with large-scale concurrent access
A number of state-owned commercial banks, national joint-stock banks and other projects have been accumulated to ensure the progress and quality of the project in terms of product and project management personnel reserves
Platform Value
Possess the enterprise's global information data, providing effective data support for management analysis and business decision-making
It has the most reliable data and unified statistical caliber, which greatly improves the efficiency of data query, especially for mass data related queries and complex queries
Analyze history, compare and summarize history better, and predict the future based on history