Data Governance Factory

It provides data integration, data development, data governance, data visualization and other capabilities to help governments and enterprises implement big data and data middle platform strategies, realize data-driven business intelligence, and promote the digital transformation and upgrading of governments and enterprises and business model innovation.

  • About the Data Governance Factory
  • Business Challenges
  • Advantages of Cloud Migration
  • Business scenarios
  • Customer cases

About the Data Governance Factory

With the goal of data empowerment, it provides one-stop data governance solution capabilities such as data development, data standards, data modeling, resource management, and data services. Through the development and governance of data, data standards, norms, and models are implemented, data quality is improved, data assets are managed, data security is ensured, and data is visualized, managed, and available.

Business Challenges

  • Data service capability improvement

    Mining the value of data and strengthening the development and utilization of data can improve the level of public services, drive social governance reform, strengthen supervision and management, improve decision-making capabilities, provide a variety of data service methods, improve data service capabilities, and help data utilization and value realization.


  • Data security

    The lack of data security will infringe on the rights and interests of personal information subjects, and affect national security, economic development, and social stability. In 2021, the Security Law of the People’s Republic of China was released, which proposes to establish and improve the data security governance system, improve the ability to ensure data security, and put forward higher requirements for data security management.


  • Data quality improvement

    With the generation of massive data, the effective use of data will inevitably bring more value, and the reliability and practicability of data directly affect whether the statistical analysis can lead to the correct conclusion. Nowadays, the current situation of multi-source heterogeneous data and inconsistent data standards has brought about data quality management problems that need to be solved urgently.


  • Massive data collection

    In the face of the rapid development of society, data is characterized by multiple types, large volume, and rapid growth; As digital transformation advances, both governments and enterprises need to carry out large-scale data collection, analysis and utilization, which has launched new challenges for data collection in terms of technology and process.


Advantages of Cloud Migration

  • Open data services

    Establish a data service system based on “data + service” to promote business innovation and jointly build a big data ecosystem.


  • Data governance operations

    Provide data standardization and standardized management to realize the visualization, management, and availability of data assets.


  • One-stop data development

    Provides a visualized one-stop data development environment to quickly complete the full-link processing of data.


  • Multi-source data aggregation

    Collect data from various sources such as databases, the Internet, and the Internet of Things to achieve massive data aggregation.


Business scenarios

  • Visual application development

  • Data collection and exchange

  • Building of an industry data lake/data middle platform

  • It provides built-in rich data visualization components to meet the requirements of business charts, dashboards, reports, and large screens, and support the visualization of business applications. It provides rich visualization components such as Sankey charts, multi-dimensional bar charts, and GIS icons. With data security management and control, it provides refined data permission management and control capabilities, and supports automatic compatibility and adaptation of multiple terminals.


  • It provides batch data migration services between homogeneous/heterogeneous data sources to support data collection, reporting, and exchange requirements of business systems. It supports a variety of heterogeneous data sources, 20+ heterogeneous data sources, and data synchronization scenarios among 400+ pairs of data sources. Multiple synchronization modes provide multiple synchronization methods, such as full-scale and incremental synchronization, and support synchronization in database log mode.


  • By applying the rich industry domain models and algorithms accumulated by the data governance factory in various business fields, it helps the industry build a data middle platform and quickly improve data operation capabilities. With multi-industry support, it covers various industries such as cities, veterans, emergency response, industrial manufacturing, and smart healthcare. With rapid application of industry models, it supports rapid application of industry governance processes, basic libraries, topic libraries, and thematic libraries.


Customer cases

Improve service levels and lead economic development with cloud computing technology,

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