Welcome to our catalyst! ------------------------ The project leverages the DataFabric concept to construct an intelligent data sharing system for data assets, focusing on addressing challenges such as difficult data asset acquisition, poor data asset quality, low data asset utilization efficiency, and slow data asset monetization. Build a data sharing platform assets to breakthrough from data acquisition to assign to the whole process of use, by swiftly establishing data connections. It provides interlinked, convenient and automatic functional applications for the whole life cycle of data assets, freeing developers' hands, enhancing business demands, expanding the scope of the digital market, and enabling the value of data. This, in turn, allows more talents to engage in creative endeavors. After the establishment of the project, China Unicom Software Research Institute organized detailed research and analysis of the status quo of data assets, overall plan design, software detailed design ,coordination work with other partners and other work . CAICT is responsible for the formulation of data asset management methods.BONC is responsible for software platform design and architecture, and completing the development and implementation of data assets and data integration functions.Baidu is responsible for providing intelligent algorithms and search engine technology for the platform, using natural language processing and machine learning to conduct in-depth analysis and index of data. AsiaInfo Technology is responsible for the construction and implementation of data asset operation functions. This project has achieved the following goals and practices: 1.Unified management of BOM multidomain data assets Open up organizational, network, and technical barriers to achieve peer-to-peer connection, build data asset catalogs and data asset mapping, and complete the main business BOM three-domain data online can be seen, checked, managed, and available. The data asset screen displays asset lifecycle data from multiple dimensions such as asset management, asset scenario operation, asset subscription, and asset usage. The screen fully demonstrates the massive data processing and analysis capabilities of the project, which includes over 47000 multidomain Data assets, 510PB storage capacity, over 3800 high-value assets, over 86000 asset references, over 30000 asset subscriptions, orver 11400000 asset push times, over 87% timeliness rate of assets push. At the same time, based on the timeliness and scenarios of frontline personnel usage, asset standardization and scenarioization were promoted through business scenarios, and more than 4000 business scenarios and 14000 customer view scenarios were summarized for frontline empowerment. 2.Building an intelligent asset catalog Utilizing technologies such as data virtualization, integration capabilities, cross-platform deployment, and orchestration to enable rapid display and retrieval of data through DataFabric. Employing knowledge graphs and artificial intelligence to achieve intelligent recommendations for data assets, transforming the traditional approach of people searching for data to data finding the right people. The use of this entire service is no longer limited to the PC. We also provide mobile services, enabling employees to grasp data dynamics anytime and anywhere, allowing data to flow at their fingertips, and delivering flexible and efficient data value transmission. 3.Integrating standards, development, governance, and operations into a unified workflow Based on the idea of DataFabric's data architecture, it builds an asset management product system to provide managers, business personnel, and developers with full-process control and openness of asset management, release, subscription, use, evaluation, and downgrade, and realizes a unified management system for data assetization. Data asset developers can develop new assets on the platform or perform secondary development on acquired data assets. With the predefined data standards on the platform, they can generate data models with a single click. Through data integration tools, they can smoothly carry out logical transformations and mappings for data processing. Meanwhile, data producers can set up and monitor processing tasks on the platform, leading to the generation of a complete data asset processing workflow within the platform. Data asset quality is of utmost concern to everyone. Data producers can ensure the timeliness, completeness, accuracy, reasonableness, uniqueness, and consistency of data through quality management. Ultimately, a data quality report is generated to guide developers and producers in quality control. Data users can also focus on the reliability of data quality, facilitating necessary quality avoidance and analysis. Data assets that pass quality validation can be published on the platform to meet the queries and usage needs of users.