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Product Briefing

Core Functions

Integration of development

It integrates requirements management, data exploration, model design, code development and test operation to form an agile data product development process.

Integration of management

Support multi-project collaborative development management, realize version management, code base management and deployment management according to different projects and requirements, and provide independent services based on data assets to meet agile data application analysis scenarios. Provide global operation monitoring management.

Integration of governance

Build a unified data asset view to closely combine metadata, data standards and data quality with development, build an integrated development and governance pipeline, and realize governance of data services.

Establish a refined operation system

Realize data line link measurement, multi-role multi-task end-to-end support, reduce labor cost, and reduce operation cost.

Unified Data Services

Service usage is manageable and monitorable. Zero code service release, low dependence on technical level, e-commerce-like data supply and demand collaboration. Provide offline bulk data service capability. Support online subscription, download and other ways of using numbers. Order takes effect online and runs automatically.

Product Structure

Product Value

Increase productivity

Establish a bank-wide data development and management platform, establish a convenient data demand processing process, comprehensively support the end-to-end work and mutual cooperation of personnel in each role in the process, and improve work efficiency.

Integration of development and management

Metadata-driven development is realized, and metadata, data standards and data quality are closely combined with development as the basis of integration of development governance.

Self-service data service

Self-service data service transforms the traditional supply-demand relationship process and supports fast data analysis and consumption mode.

Data Governance Closed Loop Process

Realize metadata change, standard formulation and failure, data quality problem discovery and processing process to form a data governance closed-loop process.