2025年，数据要素市场化改革步入"深水区"。政策持续发力，技术加速迭代，企业如何抓住数据要素带来的战略红利，将海量数据真正转化为驱动增长的 核心资产？ 由大数据技术标准推进委员会（CCSA TC601）组织百家领先企业和权威专家共同编制的《数据资产管理实践指南（8.0版）》正式发布！作 为连续九年迭代的行业"风向标"，今年的8.0版首次系统描绘了从 "数据资源化"到"数据资产化"再到"数据资本化" 的完整价值跃迁路径，是各行各业管理 者、数据从业者把握未来方向的必备工具书。 一、核心升级：首次清晰勾勒数据价值化"三级跳" 过去，我们谈数据治理，多聚焦于质量、安全和内部应用。8.0版指南明确指出，数据资产管理已发生范式跃迁： 资源化（打好地基）：解决数据"有没有、好不好、安不安全"的问题，是价值释放的前提。指南详解八大管理职能（模型、标准、质量、安全等）的内在 联系与智能化演进。 资产化（实现价值）：核心是让数据的价值"看得见、摸得着、可计量"。指南系统阐释了数据资产登记、确权、估值、成本核算、入表、内外部流通六大 核心管理活动，直击企业最关心的"如何入表"、"如何定价"、"如何交易"等实操难题。 资本化（放 ...

气象部门向全社会共享12类100余种气象数据产品，发放气象数据身份标识106万个；农机作业数据库助 力农业现代化产业发展；数据治理大模型提升企业运营效率……一段时间以来，数据在各行各业中发挥 重要作用，成为驱动经济社会高质量发展的关键资源。 完善机制，推动数据资产化。数据的价值在于使用，更在于流通与交易。推动建立数据资产登记、评 估、入账和审计制度，支持有条件的企业将数据纳入资产负债表。发展数据交易所、数据经纪商、第三 方评估机构等经营主体，构建"原始数据不出域、数据可用不可见"的安全流通机制。鼓励数据产品化， 开发数据包、数据API、数据模型等可交易产品，培育数据要素市场，推动数据从资源向资产的变化， 加速实现从"数据沉睡"到"数据赋能"的根本性转变。 强化融合应用，实现数据价值化。数据的价值最终体现在应用成效上。推动数据与人工智能、云计算、 物联网、区块链等新一代信息技术深度融合，构建"数据+算法+算力"协同体系，充分发挥数据要素的 放大、叠加和倍增作用。通过加速数据在研发设计、生产制造、经营管理、市场服务等产业链各环节的 贯通应用，赋能传统产业转型升级，催生新产业、新业态、新模式，让数据要素深度融入经济 ...

Core Insights - The 2025 "Data Element ×" competition has seen significant participation, with over 23,000 teams and more than 117,000 participants, leading to 893 projects advancing to the national finals and 183 awarded projects [1] - The competition has demonstrated breakthroughs in scale, quality, and effectiveness compared to the previous year, highlighting the increasing circulation of data through open, shared, and authorized operations [1] - The integration of public data in projects is notable, with 53% of projects utilizing public data, and over 43% of these projects adopting the new model of authorized operations [2] Data Utilization and Trading - The competition reflects a growing trend in data product and service diversity, with approximately 40% of enterprises offering subscription indices and analytical reports, and 15% providing high-quality industry data sets [3] - Data trading is becoming a crucial method for enterprises to acquire data resources, with over 50% of final projects having engaged in data trading [3][4] - The new model of authorized operations has been widely practiced, ensuring the safe and compliant use of public data while empowering enterprises to develop valuable data products and services [2] Future Directions - The National Data Bureau plans to support the establishment of a comprehensive service system for data circulation and trading, promote new models for industry data integration, and enhance the capabilities of data merchants in developing data products [4]

Core Viewpoint - The establishment of a trusted data space is crucial for addressing the three major pain points in data circulation: supply-side reluctance to provide data, demand-side hesitance to use data, and the sustainability challenges faced by platforms [1][2]. Group 1: Pain Points in Data Circulation - The supply side is hesitant to provide data due to concerns about where the data will be used and the potential loss of control [2]. - The demand side is reluctant to use data because of uncertainties regarding its source, compliance, and quality [2]. - Platforms face sustainability issues as data technologies continue to evolve, and the current business models are not clearly defined [2]. Group 2: Role of Trusted Data Space - The trusted data space is seen as a solution to the trust issues in data sharing, enabling integrated collaborative development and resource sharing to overcome data silos [2]. - Companies are increasingly recognizing the necessity of building trusted data spaces to ensure effective data supply, flow, and utilization [2]. Group 3: Practical Applications and Benefits - Trusted data spaces have demonstrated their effectiveness in reducing costs and enhancing competitiveness, particularly in industries like home textiles, where they protect intellectual property and original designs through integrated platforms utilizing blockchain and AI [3].

Core Viewpoint - Guizhou Data Exchange (贵数所) is at the forefront of data element market reform in China, having established itself as the first comprehensive big data pilot zone and data trading venue in the country, aiming to create a robust data trading ecosystem and enhance data resource utilization [1][3]. Group 1: Service Positioning and Market Coverage - Guizhou Data Exchange aims to serve a unified national market, focusing on building a national-level data trading platform and core hub for data circulation, with an emphasis on compliance and self-regulation [3]. - The exchange provides services to various market entities, including enterprises, social organizations, and government institutions, covering 20 sectors of the national economy such as agriculture, manufacturing, and transportation [3]. Group 2: High-Quality Data Sets and Partnerships - The high-quality data set area of Guizhou Data Exchange has aggregated nearly a thousand high-quality data sets from over 50 data providers, covering various modalities including text, images, and audio [4]. - Major clients include prominent companies like Huawei, Ant Group, and Tencent, indicating the exchange's significant role in the data service market [4]. Group 3: Innovations and Solutions - Guizhou Data Exchange has implemented several innovative measures to address challenges in the data market, including the establishment of 25 data zones to enhance supply and trust in data transactions [7]. - The exchange has developed the first national data product transaction price calculator, providing a credible pricing reference for data products, which is a significant advancement in the data asset pricing mechanism [8]. - It has also created a comprehensive set of data trading rules to enhance mutual trust among market participants, including guidelines for compliance and security assessments [8]. Group 4: Case Study and Economic Impact - A notable example of the exchange's impact is the successful data asset registration and trading by Benxi Steel Group, which utilized its supply chain financial data product to facilitate financing for small and medium enterprises, thereby promoting inclusive finance [6].

Group 1 - The core theme of the recent Global Digital Economy Conference is "Building Digital Friendly Cities," emphasizing the importance of global digital economic cooperation and the challenges faced by major cities in China, such as Beijing, Shanghai, and Shenzhen, in becoming global benchmarks for digital economy [1] - The transformation of digital cities is now a strategic mission aimed at enhancing national competitiveness and modernizing governance, moving beyond mere technological applications to a focus on public value [1][2] - The relationship between value and technology is crucial, where technology should serve as a means to solve urban issues and enhance citizen welfare rather than being an end in itself [2] Group 2 - The development of digital cities must address the new contradictions and core relationships, particularly focusing on data value attribution, distribution, and realization [3] - The process of data value realization involves three stages: data resourceization, data assetization, and data capitalization, each addressing different aspects of data management and economic value creation [3][4] - Cities should adopt data value management as a top-level strategy, establishing clear data ownership and efficient circulation systems, exploring equitable data revenue distribution models, and creating mechanisms for data value release driven by real-world applications [4]

Group 1 - The mayor emphasizes the importance of enhancing resource development and utilization, promoting compliant and efficient circulation of data resources, and exploring paths for data elementization, resourceization, and assetization [1] - Integer Intelligent Information Technology (Hangzhou) provides professional intelligent data engineering platforms and data set construction services for the AI industry, with applications in smart driving and smart healthcare [1] - The mayor encourages companies to focus on cutting-edge fields, quickly address market demands, accelerate key technology breakthroughs, and diversify application scenarios to drive development in the industry [1] Group 2 - Hangzhou Jinglian Cultural Technology Company builds a self-developed data processing platform, creating a "data kitchen" model to provide high-quality data products for large model manufacturers [2] - Zhejiang Fulian Technology Company is one of the first enterprises in the "reform sandbox" for data elements, with products applied in financial fraud prevention and power operation [2] - The mayor highlights the need for leading enterprises to leverage their technological advantages, continuously innovate and optimize data service products, and explore new models and scenarios for data asset operation and circulation [2] Group 3 - Hangzhou Data Exchange focuses on a compliance system, infrastructure, application scenarios, and ecological construction to explore a compliant transformation path from data resourceization to data value realization [3] - The mayor stresses the importance of top-level design, focusing on key aspects of data resourceization, and enhancing data mining and utilization capabilities [3] - There is a call to strengthen the data element industry ecosystem, innovate systems and mechanisms for data resourceization, productization, and assetization, and promote compliant and orderly data flow [3]

Group 1 - Data is regarded as the "new oil" and "new currency," becoming a fundamental engine for the deepening development of the digital economy [1] - China is enhancing its focus on data as a key factor for gaining competitive advantages in the next round of industrial competition [1][2] - The establishment of a comprehensive system for the value realization of data elements is a long-term and complex project requiring both institutional innovation and practical exploration [1][2] Group 2 - China's path to data value realization will balance safety and development, addressing the relationships between data development and regulation, security and application, as well as domestic and international considerations [2] - The inclusion of data as a production factor in the Fourth Plenary Session of the 19th CPC Central Committee has solidified its status and value enhancement [3] - Recent policies, including the Ministry of Finance's guidelines on data asset management, indicate that data assets are now recognized as important strategic resources for digital economic development [3] Group 3 - Data assetization is a key goal for maximizing the value of data resources, transforming them into a new source of economic growth [4] - The number of data trading institutions and related enterprises is increasing, with approximately 17,600 data trading companies in operation by the end of 2024, 25% of which were established within the last year [4] Group 4 - The process of data value release involves three stages: resourceization, assetization, and ultimately capitalization [5] - Data resourceization is the starting point for value release, focusing on converting raw information into manageable and reusable data assets [5] Group 5 - A successful data monetization strategy requires a closed-loop solution that aligns with national policy, industry development, low-cost investment, sustainable value growth, and high economic efficiency [6] - An example of a successful data service project involved a city investment company that invested over 3 million yuan, resulting in a data asset valuation exceeding 5 million yuan and a market value of over 30 million yuan [6][7] Group 6 - The "value cube" of data is achieved through addressing three key issues: rights confirmation, circulation, and financing [8][10][12] - The establishment of a data rights confirmation system aims to clarify ownership issues, with innovative products like the "three certificates" service for data rights [8] - A dual-driven model of government guidance and market dynamics is being developed to create an efficient and trustworthy data market ecosystem [10] Group 7 - Data asset pledge financing is a common practice that offers low-cost, efficient, and flexible solutions for financing challenges faced by small and medium-sized enterprises [12] - The construction of a data financing platform facilitates the management of data assets, ensuring compliance, quality, and value assessment [12] Group 8 - The essence of the "value cube" lies in the innovation of models, technological empowerment, and ecological collaboration, which together facilitate the realization of data value [14]