Partnering with Sunline, GBase 8a MPP built a data foundation to drive digital transformation at Bank of Handan.
GBase, together with Sunline, built a foundational data platform with a hybrid Hadoop+MPP architecture for Bank of Handan, featuring capabilities such as data ingestion, preprocessing, storage, modeling, analysis, and visualization, providing data support for the bank-wide digital transformation.
To accelerate its digital transformation, Bank of Handan established a Digital Banking Department in the second half of 2020 and launched a data platform project at the end of the year. After extensive evaluation, research, and multiple rigorous rounds of selection and testing, the bank ultimately chose GBase 8a MPP to replace its original Oracle database and successfully deployed an 8-node cluster. This enabled:
Data Development Capabilities
A unified management platform for data exchange, job scheduling, and data development, allowing better technical management and improving the efficiency of both data development and data flow.
Data Application Capabilities
A metrics management platform where indicators are managed and queried on an integrated platform.
Building a Data Staging Layer
Collection and aggregation of data from business systems, preserving original business processes wherever possible, keeping data aligned with source systems, with only minimal integration or added date descriptions.
Building a Data Model Layer
A unified data model built on source systems according to the bank’s data standards—including basic integration layer models and common processing layer models—to accumulate shared data and enforce data standards, forming a unified and standardized business data system.
Building a Metrics Aggregation Layer
Identification of common financial institution indicators based on regulatory reporting, data applications, and business management needs, creating a practical and forward-looking indicator system with at least 500 indicators operationalized on the metrics management platform.
Historical Data Migration
GBase 8a MPP helps drive comprehensive data intelligence for city commercial banks: In recent years, banking IT has made significant strides, but compared with the rapidly evolving economy and intensifying industry competition, there remain many mismatches and inconsistencies—most notably the lack of unified technical standards, limited technology adoption, and inadequate system integration. As technology evolves faster, banks face an increasing number of data analysis demands. A big data platform occupies a foundational role in building an industry standards system, linking and coordinating the whole.
GBase 8a MPP helps lower costs and improve operational efficiency: By building a standardized big data platform that seamlessly integrates industry, business, and management information, the bank enables data integration and resource sharing, fostering orderly communication and interaction, and boosting the efficiency of report generation and usage. This lays the groundwork for integrated, data-driven intelligence and decision-making, reducing costs and improving resource allocation.
GBase 8a MPP enhances management capabilities and resource control: Statistical and analytical data serve as critical sources and foundations for both macro and micro management. A unified big data platform provides a shared intelligent data analysis system for business management and tracking across the bank, aligning data and workflows between departments. It effectively eliminates duplicate data sources, inconsistent metrics, and redundant reporting, significantly reducing administrative costs, strengthening monitoring effectiveness, and elevating decision-making and management.
Once again, GBase database has earned customer recognition, helping Bank of Handan’s data platform advance another step while achieving technology independence through indigenous innovation. The fully self-developed GBase 8a MPP offers unmatched strengths in cluster architecture, high availability, high concurrency, scalability, virtual clusters, resource management, active-active clustering, and data synchronization across homogeneous and heterogeneous clusters.