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Industry SolutionsData Governance Platform Project for a Leading Financial Institution
The client previously relied on a small number of IT personnel to manually manage metadata generated across numerous systems. This approach limited data discoverability and sharing, while simultaneous manual maintenance by multiple stakeholders often led to inconsistencies and errors. To strengthen enterprise data capabilities, ensure data quality, and meet compliance requirements, the client urgently needed to establish a formal data governance framework and pursue sustained implementation.
Inaccurate and duplicate data
Lack of standardized data definitions
Absence of structured data modeling practices
No closed-loop tools or mechanisms for data quality management
Centered on data quality, GienTech developed a comprehensive data governance platform and framework. The platform enables centralized management of data standards, metadata, and data quality, and presents data assets through a unified portal that supports asset search and discovery.
Supports the maintenance and governance of foundational and applied subject data standards, as well as the definitions of core data indicators. Key features include browsing and revision of standard documents, version control, and comparative analysis of changes.
Implements rule-based data quality checks to identify and address quality issues across enterprise systems. Provides continuous monitoring of data quality trends and rule coverage, and generates regular reports on key data quality metrics.
Includes four major modules: metadata analysis, acquisition management, lifecycle management, and version control. Offers full lifecycle support for metadata operations such as creation, editing, deletion, and querying. Also supports version management—including versioning, version comparison, and impact analysis. Lineage analysis tools help trace data flows and assess the downstream impact of changes.
The platform, with metadata management at its core, ensures unified governance of data standards and quality. This guarantees the integrity, consistency, accuracy, and uniqueness of enterprise data. By exposing data assets through a centralized portal and enabling search capabilities, the platform empowers better data understanding and application. It enhances the institution’s data governance maturity, helps fulfill regulatory expectations, and positions the enterprise to leverage data effectively in an increasingly competitive and data-driven financial landscape.
中电金信鲸Bot RPA是一款面向金融行业客户的机器人流程自动化的开发平台。
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鲸Bot设计器
鲸Bot设计器集成了浏览器自动化组件，office办公自动化组件，数据库组件，文件处理组件、邮件组件等多种类型组件，通过全栈自动识别技术，自动识别目标元素，使开发过程所见即所得，降低了RPA开发门槛，让业务人员也可以方便地进行业务流程的开发。
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鲸Bot机器人
通过手动执行、定时执行、控制台远程调用的方式运行自动化流程，配合控制台对外提供API接口，供外部程序调用。通过特有的视觉反馈技术提供统一的异常处理机制，极大降低开发和运维成本，让RPA流程运行更加稳定，而解决金融行业因技术人员产能不足难以支持其业务发展的问题。
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