Recently, at the "China Data Management Summit" organized by the International Data Management Association (IDMA), both the Beijing headquarters and the Shanghai headquarters of China Economic Information Service (hereinafter referred to as "CEIS") were awarded the annual "Best Practice Award for Data Elements" and "Best Practice Award for Data Governance," respectively. This not only recognizes CEIS's professional capabilities in the field of data governance but also affirms its contributions in promoting the marketization of data elements, fostering the development of the digital economy, and leading big data services across various industries.

The International Data Management Association () is a global nonprofit professional organization dedicated to data management and digital transformation. The annual Data Governance Award aims to recognize and encourage organizations and individuals who have made outstanding contributions in the field of data governance, set benchmarks for data management across various industries, and promote the development and innovation of domestic data governance.

The "Best Practices in Data Elements Award" is presented to outstanding teams in the industry who have dedicated themselves to the field of data asset valuation and trading, conducting systematic research and practice in areas such as data asset ownership, valuation, entry into financial statements, and trading, and achieving significant results. China Economic Information Service (CEIS) initiated the data asset entry into financial statements at the end of the year, comprehensively sorting out and conducting compliance reviews on existing data resources, ensuring the compliance and flawlessness of data resources, and classified the profit models of existing products and services. Through historical cost aggregation, CEIS successfully completed the data asset entry into financial statements. Additionally, CEIS established the Data Asset Operation Research Center, based on its own entry practice, independently created the "Five-Step Method for Data Asset Entry into Financial Statements," and authored the "Practical Guide to Data Asset Entry into Financial Statements in the Economic Information Service Industry," providing feasible paths for enterprises, which has been widely acclaimed.

The "Best Practices in Data Governance Award" is presented to organizations and individuals who have made outstanding contributions in the field of data governance. The Shanghai headquarters of China Economic Information Service leverages its technical expertise to create an "Industry Insight" industrial data service platform centered on the industrial chain map, by connecting the "macro" - "industry" - "park" - "enterprise" data relationships. This platform aims to assist government departments, financial institutions, and enterprise groups in integrating internal and external industrial data, constructing business-driven industrial insight scenarios, enhancing the service capabilities of business departments for enterprises, and achieving data-driven business growth and industrial planning development. Relying on the big data innovation service capabilities of the Industry Insight industrial data service platform, the Shanghai headquarters has successfully provided services to leading financial institutions such as the Bank of Communications and Shanghai Pudong Development Bank, as well as multiple local government economic departments, receiving high praise from users.

The simultaneous awards received by both the Beijing headquarters and the Shanghai headquarters of CEN fully demonstrate CEN's professional capabilities and innovative practices in data governance and data asset inclusion, highlighting CEN's strong influence in the entire data element industry chain. As data assetization and data business continue to deepen, "digitalization" has become a new engine driving the high-quality development of CEN's economic information business. CEN will continue to leverage its professional strengths to create value in the fields of data governance and data asset management.