Core Viewpoint - The implementation of the Ministry of Finance's "Interim Provisions on Accounting Treatment of Enterprise Data Resources" in 2024 marks a significant shift in recognizing data assets as a vital component of corporate value in the digital economy, while companies face challenges in integrating these assets into their financial statements [1] Group 1: Challenges in Data Asset Integration - One of the main obstacles for companies in recognizing data assets is the conflict between accounting practices and traditional systems, along with a lack of operational processes for cost allocation [2] - The "Guidelines" provide a systematic framework for cost collection and allocation related to data resources, clarifying the main components such as procurement, processing, and development costs, and innovatively categorizing costs into directly attributable and indirect expenses [2] Group 2: Legal and Compliance Framework - The "Guidelines" bridge the gap between compliance and accounting recognition by addressing the complexities of data asset ownership, which is more intricate than traditional assets [3] - A comprehensive solution is provided for compliance and ownership verification, requiring companies to conduct thorough self-assessments and implement measures to clarify their rights to data resources [3] Group 3: Strategic Management and Value Creation - The "Guidelines" elevate the discussion of data asset recognition beyond mere accounting, emphasizing the importance of aligning data integration with corporate strategic goals to activate data value and drive high-quality development [4] - Companies are encouraged to disclose non-financial information regarding data resource applications and value creation, enhancing financial report transparency and promoting a shift from viewing data as a cost to recognizing it as a value driver [4] Group 4: Broader Implications and Future Outlook - The "Guidelines" reflect the Ministry of Finance's macro policy leadership while providing a scientific summary of regional practices, offering a model for replication in other areas [5] - The establishment of a robust accounting ecosystem for data assets will depend on cross-industry and cross-regional data circulation and value assessment, requiring higher-level institutional coordination [5]

Core Viewpoint - The implementation of the "Interim Provisions on Accounting Treatment of Enterprise Data Resources" by the Ministry of Finance in 2024 marks a significant shift in recognizing data assets as a vital component of corporate value in the digital economy, while companies face challenges in practical application due to issues like ownership definition and value measurement [1][5]. Group 1: Challenges in Data Asset Accounting - One of the main obstacles for companies in accounting for data assets is the conflict with traditional accounting systems and the lack of operational processes. The "Guide" provides a framework for cost collection and allocation related to data resources, clarifying the main components such as procurement, processing, and development costs [2]. - The "Guide" innovatively categorizes costs into directly attributable costs like "data ownership verification fees" and "quality assessment fees," as well as indirect costs such as "infrastructure costs" and "human resource costs," offering clear guidelines for their allocation [2]. Group 2: Bridging Compliance and Accounting - The "Guide" effectively addresses the gap between compliance verification and accounting recognition, emphasizing that the ambiguity in ownership is a fundamental barrier to data assetization. It outlines a systematic solution for compliance and ownership verification, requiring companies to conduct comprehensive self-checks [3]. - The "Guide" translates the "three rights separation" concept from the "Twenty Articles on Data" into actionable steps, detailing how companies can clarify their ownership rights through contracts, technical means, and registration [3]. Group 3: Strategic Integration of Data Assets - The "Guide" transcends mere accounting techniques by positioning data asset accounting within the broader context of corporate strategic management and value creation. It emphasizes that data asset recognition should align with corporate strategic goals and encourages analysis of the commercial value and financial contribution of data resources [4]. - Companies are urged to consider factors such as business models, update frequency, and technological iterations when estimating the useful life of intangible assets, linking accounting treatment closely with economic substance and business lifecycle [4]. Group 4: Broader Implications and Future Directions - The "Guide" reflects the Ministry of Finance's macro policy leadership while providing a scientific summary of regional practices, offering a replicable model for other areas. However, it acknowledges that a local guideline cannot resolve all issues in the marketization of data elements [5]. - The formation of fair value for data assets relies on cross-industry and cross-regional data circulation and value assessment, necessitating higher-level institutional coordination. Future local explorations may help build a data asset accounting ecosystem that aligns with national conditions and international standards, positioning data as a new engine for high-quality economic development [5].

Core Insights - The first Qinghai Data Element Ecological Conference will be held on September 21, focusing on the construction of a data element ecosystem in Qinghai, which is a significant step in implementing the national "data element ×" three-year action plan and participating in the Belt and Road Initiative [1][2] - Qinghai aims to integrate its unique resource endowments and strategic positioning to promote the deep integration of the real economy and the digital economy, supporting the new era of western development strategy [1] - The conference will serve as a platform for policy interpretation and development trend analysis, featuring key experts discussing the role of data elements in driving industrial upgrades and economic transformation in Qinghai [2] Group 1 - The conference is co-hosted by multiple government departments and aims to build a cross-regional collaboration platform to unleash data value for high-quality development in Qinghai and the western region [2] - Qinghai is leveraging its clean energy advantages, such as solar and wind power, to establish a comprehensive computing power supply system, enhancing its competitive edge in the national data element layout [1][2] - The event will include a special seminar on "Data Empowering Industrial Development," focusing on the transformation of data from resources to assets and capital, with discussions on compliance and data asset integration [3] Group 2 - The conference will showcase various initiatives, including the unveiling of the Qinghai Data Element Circulation Service Innovation Center and the launch of a talent cultivation plan for data elements in Xining [3] - Experts from renowned data groups and technology companies will share advanced experiences and case studies to promote the deep integration of Qinghai's advantageous industries with data elements [3] - The discussions will also address the intelligent transformation of traditional industries and innovations in artificial intelligence applications, aligning with Qinghai's unique characteristics [3]

Core Viewpoint - The integration of digital technology into various sectors has made data a key production factor alongside labor, land, capital, and technology, emphasizing the need for effective data assetization to drive high-quality economic development [2][7]. Group 1: Data as a Production Factor - Data must undergo systematic processing, such as collection, cleaning, and labeling, to transform from raw data into valuable production factors [3]. - Despite the growth of China's digital economy, successful utilization of data resources is primarily seen in internet platform companies, with insufficient inter-organizational and market data circulation [3][4]. Group 2: Challenges in Data Value Realization - Several constraints hinder the trading and circulation of data, including unclear ownership, scene-dependent valuation, and security concerns [4]. - Companies often prefer internalizing data services rather than engaging in market transactions due to security and ownership issues [4]. Group 3: Current Practices and Innovations - Various organizations are exploring data resource integration and productization, leading to the emergence of data trading institutions and successful case studies [5][6]. - Data products are evolving into standardized datasets, analytical reports, and decision models, enhancing the measurement of data value [5][6]. Group 4: Future Directions for Data Value Realization - The realization of data value is crucial for strengthening the digital economy and promoting the synergy between industrial digitalization and digital industrialization [7]. - Emphasis should be placed on improving data collection, management, and sharing mechanisms across different sectors to fully unleash the potential of data as a production factor [7].

Core Viewpoint - Jining City is actively promoting high-quality development through digital transformation, focusing on the goals of "one trillion, fivefold increase" and implementing a comprehensive digital strategy to enhance various sectors of the economy [1] Group 1: Industry Development and Innovation - Jining is concentrating on industrial development to expand the scale of the digital economy, leveraging the provincial digital economy innovation development pilot zone to implement ten major digital industrialization projects and eight actions for industrial digital transformation [2] - The city has established a digital economy project database with 317 key projects, including significant initiatives like the Shandong Times New Energy Battery Base and the Kobot Drone Production Base, which are expected to drive digital economic growth [2] - Jining is enhancing enterprise support by organizing various industry events and establishing a list of enterprise issues to address challenges related to talent, funding, and policy, resolving 43 specific requests [2] Group 2: Data Utilization and Market Reform - The city is advancing the new generation of information technology industry, achieving a revenue growth rate of 22% from January to July, and implementing ten plans to support project landing and market entry [3] - Jining is focusing on data element value release through a pilot program for comprehensive data element market reform, successfully integrating core data types into the provincial public data resource platform and creating 130 high-quality data sets [3] - The establishment of a data service provider alliance has facilitated data asset registration and evaluation for 44 companies, with a total data transaction scale exceeding 200 million [3] Group 3: Data Application and Innovation - Jining is promoting data element integration in industrial manufacturing and logistics, successfully hosting competitions and creating 208 application cases, with 36 advancing to the provincial finals [4] - The city aims to create a national-level data industry development cluster, showcasing innovative applications of data in various sectors [4] Group 4: Digital Governance and Infrastructure - Jining is enhancing digital governance capabilities through integrated reforms in digital government, improving efficiency in public services and enterprise support, resulting in a 90% reduction in business processing steps and an 81% decrease in processing time [5][6] - The city has established 18,078 5G base stations and 21 data centers, with a total computing power of 1260P, supporting the digital infrastructure necessary for economic growth [6] - Jining is committed to deepening the integration of the real economy and digital economy, aiming to contribute significantly to the province's green and high-quality development [6]

Core Insights - The article highlights the successful registration of multiple large models in Qingdao, including the "Zhuo Shu" model developed by Inspur (Shandong) Big Data Technology Co., Ltd, which aims to activate the potential of data elements in various key sectors [1][2][3] Group 1: Company Developments - Inspur's "Zhuo Shu" model has been applied in enterprise credit, macroeconomics, and grassroots governance, showcasing its versatility across multiple scenarios [1] - The "Qi Zhi Kong Ming" model by Innovation Qizhi is tailored for the manufacturing sector, supporting various industrial applications such as text perception and data analysis [1] - The "Tian Zhi" model from Kaos focuses on industrial applications, excelling in industrial scene analysis and knowledge Q&A [2] Group 2: Industry Initiatives - Qingdao has implemented the "Moli Qingdao" three-year action plan to accelerate the development of a large model ecosystem, promoting a structured approach to model registration and evaluation [2][3] - The city aims to strengthen scenario application demonstrations and create benchmarks for vertical model empowerment to drive large-scale applications [3] - Efforts are being made to foster an open ecosystem that encourages algorithm open-sourcing, data sharing, and service openness, contributing to a vibrant open-source collaborative environment [3]

Core Viewpoint - The company has demonstrated strong business resilience despite external market pressures, with a focus on data intelligence and artificial intelligence development. Group 1: Financial Performance - In the first half of 2025, the company achieved operating revenue of 218 million yuan, with over 85% of revenue coming from data value realization-related activities [1] - The company’s main business has shown steady growth, indicating a solid foundation in the data intelligence sector [1] Group 2: Business Development - The developer services segment continues to solidify its industry-leading position, supported by a large active user base [1] - The commercial services sector is stabilizing, with positive growth potential in both enhanced services and brand services [1] - The public services division is advancing mature products while actively exploring new intelligent products, engaging in co-creation with clients [1] Group 3: Artificial Intelligence Initiatives - The company has increased its investment in artificial intelligence, establishing an AI division and appointing a Chief AI Officer, with around 50 key personnel dedicated to AI product development and technological breakthroughs [2] - The company has launched the "GAI" series of intelligent products and introduced a high-end model device for enterprise markets, forming a closed-loop system [2] - The "Data Station" strategy aims to connect various stakeholders for secure and efficient data flow, with the "Hundred Cities, Hundred Scenarios" co-creation plan already implemented in multiple cities [2] Group 4: Future Outlook - The company is committed to accelerating industry development through "data + intelligence" and plans to increase exploration in the AI field [3] - New AI-related businesses are expected to enter a promotional phase in the second half of the year, following product development and initial customer engagement [3]

Core Insights - The article emphasizes the importance of data as a key production factor, comparable to land and capital, with predictions indicating that a 10% increase in data flow can lead to a 0.2% GDP growth [1] - The construction of a data market is identified as a crucial pathway for advancing the digital economy in China, with a projected data production total of 41.06 ZB by 2024 [1] Data Market Overview - The data market consists of raw data, processed data, and standardized data service products, with diverse supply sources including businesses, government agencies, and data brokers [2] - The demand for data spans various sectors, including enterprises for marketing and risk management, and government for urban governance and policy-making [2] Differences from Traditional Markets - Data markets differ from traditional markets primarily in pricing and trading mechanisms, with various pricing models such as pay-per-use and subscription [3] - Innovative trading modes include platform trading, over-the-counter trading, and data sharing pools within data alliances [3] Regulatory Framework - Establishing a data market requires a robust regulatory framework, including standardized data classification and a unified data language to facilitate transactions [4] - The recent policy direction from the Chinese government highlights the need for clear data ownership, market transactions, and rights protection [4] Cultivating Data Operators - Data operators, or "data merchants," are essential for the development of the data market, providing services in data production, management, and trading [5] - Encouraging the opening of high-value public data and integrating data resources into asset management systems are key strategies for fostering data operators [5] Infrastructure Support - The transaction of data requires foundational infrastructure, including network, computing, and security facilities, to enable safe and efficient data flow [6] - A multi-layered data market system is proposed to facilitate data movement across regions and sectors [6] International Cooperation - Expanding into international data markets is crucial for enhancing China's digital competitiveness, necessitating the integration of cross-border data flow into economic development plans [7] - Collaboration on data protection legislation and standards is essential to balance data sovereignty with global data sharing [7]

Investment Rating - The industry investment rating is "Positive" and maintained [8] Core Insights - The Shanghai Data Exchange has introduced a new paradigm called RDA (Real Data Assets), leveraging blockchain technology to convert physical assets and intangible data elements into digital forms, addressing five key challenges in the financialization of physical assets: authenticity, transparency, liquidity, economy, and consensus [2][6] - RDA emphasizes the integration of real-world assets (RWA) with data, facilitating the deep integration of the real economy and the digital economy. The market for RWA has grown significantly, from $300 million at the end of 2021 to over $19 billion by the end of March 2025, highlighting the potential for asset tokenization [6] - The new paradigm of RDA is expected to accelerate the marketization and valuation of data elements, benefiting the entire industry chain. It suggests focusing on investment opportunities in data infrastructure, blockchain technology, and data rights and trading [6][10]

Investment Rating - The industry investment rating is "Outperform the Market - A" [6] Core Viewpoints - The report introduces the RDA (Real Data Assets) paradigm, aiming to bridge cryptocurrency and data elements, emphasizing the marketization and value realization of data elements, and enhancing the efficiency of connecting physical assets and capital [2][3][4] - RDA is positioned as the soul of RWA (Real World Assets), facilitating the mapping of physical assets in the digital realm and providing four funding channels: credit financing, equity financing, securitization, and global fundraising [3][15] - The report suggests focusing on companies related to the Shanghai Data Exchange, including YunSai ZhiLian, Shanghai Steel Union, Wanda Information, and others, as potential investment opportunities [3][17] Summary by Sections Industry Performance - The computer industry index increased by 3.37% this week, outperforming the Shanghai Composite Index by 2.28 percentage points [18][19] - The report highlights that the computer sector's performance is closely tied to themes surrounding stablecoins and related industries [22] Market Overview - The report notes that the RDA paradigm addresses challenges in ensuring the authenticity and transparency of assets during the on-chain process, leveraging blockchain technology and trusted data spaces [4][17] - The report emphasizes the importance of data authenticity in the value realization process, with RDA focusing on the integration of data and physical assets [14][16] Key Industry News - The report mentions significant advancements in AI and quantum computing, including the launch of Kimi's new model and the "Zuchongzhi 3" quantum computing prototype, which showcases China's technological prowess [25] - It also discusses strategic collaborations in the stablecoin space, such as the partnership between Jin Yong Investment and AnchorX to explore the application of stablecoin AxCNH [25]