Data warehouse system of xx state-owned commercial bank
xx state-owned commercial bank, a central financial enterprise, was established in 1994 and is a policy bank directly under the leadership of the State Council. In December 2008, it was restructured into xx Bank Corporation. In March 2015, the State Council clearly defined xx state-owned commercial bank as a development financial institution. Xx state-owned commercial bank is also the largest policy bank in China, providing financial guarantee for key national construction projects and undertaking important functions of macroeconomic regulation and control.
In the current market environment, in order to effectively improve customer service level, strengthen risk management and control ability, improve business performance and ensure sustained profit growth, banks are constantly adopting new technologies and innovating new businesses in order to gain a foothold in the fierce competition. Under such circumstances, the data warehouse effectively integrates the bank's data, conducts in-depth mining, and analyzes current and historical business data and relevant data of relevant environments. Automatically and quickly obtain the useful decision-making information, so that the bank's decision-makers can timely grasp the operation and development trend of the enterprise, improve the bank's fine management and scientific decision-making ability, provide fast, accurate and convenient decision-making support to the bank, and provide a new opportunity to the bank's business development.
Data warehouse project, which undertakes the functions of centralization, integration and application of the main business data of the whole bank, will provide unified, accurate and timely data support to the business activities such as customer management, precision marketing, risk management, financial performance, business analysis, regulatory submission, and auditing.
Data warehouse is a centralized, complete and consistent data platform of the whole bank, which collects data from multiple data sources through data extraction and cleaning. It is an integrated, current or near-current, constantly changing and standardized data set for business fields (such as deposits and loans), including current full-scale source data, incremental source data and historical source data, which is used to support the daily operation and management of the business system of the Bank.
Specific objectives are:
(a) Building an enterprise data storage center with data warehouse as the core
Use enterprise-level data warehouse storage and enterprise-level data model to integrate data from multiple business systems. According to the theme and paradigm of data warehouse and the strategy of retaining long-term historical detailed data, it provides a solid statistical analysis data foundation to the follow-up bank application services in various fields.
While building the enterprise-level data warehouse, it is necessary to build the necessary technical modules of the enterprise-level data warehouse, including a unified data integration system; unified data exchange system; unified data governance system; unified data supplement platform; unified ETL scheduling system; unified data storage and unified data processing system; these technical modules are the foundation of data warehouse.
(B) Building enterprise application infrastructure
Xx state-owned commercial bank requires that the establishment of data warehouse must adapt to the current hardware environment, be able to match the current system software environment, and make full use of the human resources and stage achievements already invested by xx state-owned commercial bank. In order to ensure the continuity of existing applications of xx state-owned commercial bank, targeted migration of applications running on existing data is required. And support the supervision and submission of data fairs, comprehensive report fairs, performance appraisal fairs, customer management data fairs, risk data fairs, financial and management accounting data fairs and other data fairs. It also supports data marketplaces such as regulatory submission data marketplace, comprehensive report data marketplace, performance appraisal data marketplace, customer management data marketplace, risk data marketplace, financial and management accounting data marketplace, etc.
Xx state-owned commercial bank also proposed to build an omni-directional, multi-level, report platform and management cockpit platform for management decision-making services, so as to realize the docking of report and management cockpit system with the core of data warehouse and various marketplaces of data warehouse. At the same time, the index system of key business systems is constructed for management decision-making levels at all levels, and the data standards of index classes are established. Based on the index system, the management decision-making levels are served through the management cockpit platform.
Overall system architecture design:
According to the actual situation of data warehouse system construction of xx state-owned commercial bank, the whole system is designed as a multi-layer and extensible framework. The core of the architecture includes data source, integrated data area (post source model layer, theme model layer, common processing layer and business capability layer), and application service area (service layer, application layer and user access layer). In addition, data warehouse data management (data warehouse data quality management, data warehouse metadata management, data warehouse data life cycle management) and data warehouse security management are also essential parts of the system, which will involve all core levels.
The following figure include in this solution
1. Data management of data warehouse
Definition: Relying on the data management platform, deploy data warehouse related data management functions;
Job description: The data quality management of the data warehouse is engaged in the pre, in-process and post process of checking the data quality of various business and technical dimensions for each data level in the data warehouse. Track and analyze the verification results, track and solve the data quality problems found in the data warehouse, and form the data quality report in the data warehouse; Metadata management of data warehouse, with the support of metadata management tools of xx state-owned commercial bank, regularly collects and maintains business and technical metadata in the data warehouse platform and its external interfaces, etc., to ensure the accuracy and consistency of metadata of each node in the data flow direction, ensure smooth data veins in the data warehouse platform, and support the influence and blood relationship analysis functions of the data warehouse platform; Data warehouse life cycle management, analyze each platform, define the principles of its data life cycle, and put forward requirements.
2. Safety management of data warehouse
Definition: Realize warehouse safety management by relying on the unified operation and maintenance monitoring platform in the bank and related software and hardware functions of data warehouse;
Job description: Data warehouse security management includes data security, data storage security, database operation authority management, data backup strategy, desensitization of information content, data encryption, data integrity, non-repudiation, etc. ;application security, user identity authentication, authorization, key security, etc; system security, operating system security, software legitimacy authorization, anti-virus, program and application backup, etc.; network security, access control, vulnerability monitoring, intrusion detection, content filtering, etc.; link security, physical layer security control of network transmission, etc. ; physical security, hardware equipment, environmental security, disaster recovery and backup, etc.; scientific safety management system and regulations.
3. Data source area.
The data source system includes the main business systems of xx state-owned commercial bank at present, and needs to meet the data requirements of the theme application of data warehouse in this phase, mainly including but not limited to the following systems:
•General ledger system
•Financial sharing system
• Rater system
•Full process credit system
• Customer relationship management system
• Hong Kong core system
• Domestic factoring system
• Student Loan System (University)
• Student loan system (place of origin)
• Unified authorization system
• Small and medium-sized enterprise system
• Online banking system
• Management accounting system
• RMB guarantee system.
• Hong Kong International Settlement system
• Hong Kong capital system.
4. ODS platform
Definition: Support the data storage of post source storage layer and provide external data services;
Job description: The ODS platform supports the requirement of quasi-real-time data, including quasi-real-time data, recent incremental data, recent snapshot data and short-term historical data.
5. Data warehouse platform
Definition: responsible for supporting model storage and data service of theme model layer, common processing layer and business capability layer; meet the data storage and services required by active data exploration and model laboratory;
Job description: for the theme model level, referring to the banking integration model system, the theme design is carried out from several dimensions of domestic banks, overseas banks, rural banks and holding companies, and the ideas and principles of a set of conceptual models and two or more sets of logical models can be referred; the common processing layer refers to the use of the calculation rule engine to summarize and process the data according to the dimensions of domestic, overseas, villages and towns and holding companies, and process the group's comprehensive summary data on this basis; the business capability layer is divided into eight business capabilities according to the characteristics of xx state-owned commercial bank, including customer marketing and channel management, product and service management, asset and liability management, risk management, financial and performance management, operation management, compliance management and strategic decision management; data service, which provides data services through various interface forms according to the actual application requirements.
6. Application service area.
Technical services provided by service layer include intermediate service applications such as report query service, application service, active exploration service and data mining service. This layer provides various services to users to access the data platform, thus realizing diversification of access methods and transparency of information access.
The application layer provides application services including CRM application, performance appraisal application, assets and liabilities, management cockpit, credit risk, management accounting, unified report and data warehouse portal.
The user access layer includes various end users. According to the ways and characteristics of users using this system, they can be divided into head office and branch users, overseas branch users, subsidiary users and external users, etc.
According to the requirements of semantic layer, this part is designed to be open to business personnel in view. All tables and fields in the view are marked with business terms or indicator names familiar to business personnel, and the business terms or indicator names are designed with reference to data standard definitions.
By 2021, after years of construction and development, the data warehouse of xx state-owned commercial bank has well supported various key applications such as unified report, regulatory submission, risk management, financial supervision and executive cockpit, which laid a solid information foundation for the bank's good operation and subsequent development. Data warehouse is divided into two dimensions: data warehouse basic platform and each marketplace. The basic platform includes five aspects: temporary layer, basic layer, summary layer, service layer and semantic layer, which are stored in various modes, such as data buffer, theme model data, summary data, view service data and semantic information data, so as to meet the requirements of data warehouse stability, sub-theme, storage history and so on.
Up to now, the systems that have been warehoused by xx state-owned commercial bank mainly include 26 systems such as core system S01, grass-roots business system-student loans from places of origin S03, grass-roots business system-college student loan S04, evaluator system S05, workflow system S06, commercial bill system S07, general ledger system S08, financial sharing system S09, human resources system S10, capital business system S11, SME credit management system S12, full-process credit system S13, international settlement system S15, CRM system S16 and asset classification system S17, covering the main business information of the whole bank.
Submit your request and we will contact you as soon as possible
Submit your request and we will contact you as soon as possible
After logging in, you can experience online demo for free, download solutions and case white papers