Data Architecture Consulting_Consulting & Service

Service Overview

GienTech Data Architecture Consulting is an end-to-end solution developed through years of consulting and implementation experience in banking data platforms, data asset management, and data services. It systematically plans each stage of data flow to continuously enhance and empower bank data capabilities, covering data collection, integration and storage, asset management, development, and service sharing.

Data Collection and Exchange Capabilities | Designed to accommodate growing user bases and data volumes, the platform lays the foundation for long-term data asset accumulation. It supports multiple data sources and collection methods, enabling full-lifecycle data acquisition throughout product usage. By capturing a comprehensive range of attributes, dimensions, and metrics, it ensures the creation of high-quality data assets.

Data Collection and Exchange Capabilities | Designed to accommodate growing user bases and data volumes, the platform lays the foundation for long-term data asset accumulation. It supports multiple data sources and collection methods, enabling full-lifecycle data acquisition throughout product usage. By capturing a comprehensive range of attributes, dimensions, and metrics, it ensures the creation of high-quality data assets.
Data Integration and Storage Capabilities | Capable of ingesting, transforming, and storing data from diverse internal and external sources, the platform breaks down data silos to achieve centralized data consolidation. It enables cross-domain business insights by organizing data around subject areas or business functions, supporting integrated decision-making across multiple domains. Cleaned and integrated data is stored in a unified manner for consistent access and use.

Data Integration and Storage Capabilities | Capable of ingesting, transforming, and storing data from diverse internal and external sources, the platform breaks down data silos to achieve centralized data consolidation. It enables cross-domain business insights by organizing data around subject areas or business functions, supporting integrated decision-making across multiple domains. Cleaned and integrated data is stored in a unified manner for consistent access and use.
Data Asset Management Capabilities | Through a comprehensive data asset catalog, the platform maps out enterprise-wide data assets, clarifies data ownership, and assigns governance responsibilities—resolving potential disputes over data usage. It ensures data security and promotes sharing through holistic governance across metadata management, data standards, data quality, and data security.

Data Asset Management Capabilities | Through a comprehensive data asset catalog, the platform maps out enterprise-wide data assets, clarifies data ownership, and assigns governance responsibilities—resolving potential disputes over data usage. It ensures data security and promotes sharing through holistic governance across metadata management, data standards, data quality, and data security.
Data Development and Management Capabilities | Supports full-cycle project and requirement management. Enables development of offline and real-time data processes, including ETL workflows. Provides unified data model management to enhance consistency and maintainability across development efforts.

Data Development and Management Capabilities | Supports full-cycle project and requirement management. Enables development of offline and real-time data processes, including ETL workflows. Provides unified data model management to enhance consistency and maintainability across development efforts.
Scheduling and Operations Capabilities | Offers robust task scheduling features during the data development lifecycle. In the operations phase, it provides monitoring tools for both data processes and computing resources, supporting stable and efficient system performance.

Scheduling and Operations Capabilities | Offers robust task scheduling features during the data development lifecycle. In the operations phase, it provides monitoring tools for both data processes and computing resources, supporting stable and efficient system performance.
Data Service and Sharing Capabilities | Delivers flexible data services tailored to users’ roles and needs, with strategic control over access and delivery. Key service models include online data services, data subscriptions, curated datasets, and data APIs—ensuring accessible, on-demand data usage across the organization.

Data Service and Sharing Capabilities | Delivers flexible data services tailored to users’ roles and needs, with strategic control over access and delivery. Key service models include online data services, data subscriptions, curated datasets, and data APIs—ensuring accessible, on-demand data usage across the organization.

Case Studies

Data Architecture Planning for a Financial Institution

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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。

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。

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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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。