Core Insights - The domestic data factor industry is evolving towards a higher value "government-industry linkage" model, driven by policy guidance and industrial construction [1] - The digital economy's core industries are becoming significant drivers of the overall economic system, with the data factor market expected to exceed 300 billion yuan by 2028, growing at a compound annual growth rate (CAGR) of approximately 20.26% [6] - The establishment of a data value circulation system is crucial for the efficient flow of data assets, with a focus on compliance and rights confirmation [11][13] Policy Analysis - The improvement of the data industry value chain and local data systems is essential for the circulation of data factors, marking a new phase of quality enhancement in the digital industry [3] - The "Data Twenty Articles" policy has initiated the construction of a data ownership system, which is vital for the efficient circulation of data value [11] Market Scale - The digital economy in China has grown from 27.2 trillion yuan in 2017 to 53.9 trillion yuan in 2023, with a CAGR of about 12.07% [6] - By 2025, the overall scale of the data factor industry is expected to reach around 200 billion yuan, with data processing and analysis becoming the largest segment, projected to reach 144 billion yuan by 2028 [6] Data Value Chain Circulation - The construction of a data value circulation system is supported by advanced technology and regulatory compliance, focusing on the phased development of data value [8] - Data asset registration is crucial for the division of ownership and promoting the market circulation of data assets [13] - The establishment of a data evaluation policy framework is necessary for the accurate assessment of data value, which is essential for market circulation [16][17] Capitalization of Data Assets - The entry of data assets into financial statements marks a significant step in the capitalization of data factors, with the implementation of regulations starting January 1, 2024 [19] - The market for data asset transactions is characterized by a "cold inside, hot outside" distribution pattern, with off-market transactions dominating due to their flexibility [21] Industry Practices - The financial sector is expected to see a CAGR of approximately 19.06%, reaching over 100 billion yuan by 2028, driven by the integration of diverse data [32] - The industrial manufacturing sector is projected to grow at a CAGR of about 24.22%, with a focus on high-quality data sets and trusted data spaces [35] - The healthcare industry is anticipated to grow at a CAGR of around 23.69%, emphasizing the compliance and security of personal health data [37] Trends - The construction of high-quality data sets is crucial for the development of the artificial intelligence industry, transitioning from "point breakthroughs" to "holistic development" [40] - The establishment of trusted data spaces will be fundamental for ensuring the circulation and high-value application of data factors [43]

Core Insights - The survey conducted by Shupeng Technology and the Public Data Alliance highlights the growing recognition among enterprises of the importance of a trusted data space for enhancing data security, facilitating cross-organizational data flow, and promoting data element operations [1][2] - A significant 70% of surveyed enterprises plan to initiate the construction of a trusted data space in the near future, indicating a strong market trend towards this infrastructure [1][12] Group 1: Motivation and Demand - The primary driver for the construction of trusted data spaces is top-down policy support, cited by 66.7% of respondents, followed closely by self-development needs and collaborative ecosystem building, each at 63.0% [4] - The most urgent demand scenario identified is achieving cross-organizational data flow, with 66.7% of enterprises prioritizing this need, followed by data element operations at 63.0% [7] Group 2: Challenges and Technology Selection - The main challenge faced in building trusted data spaces is the high cost and resource investment, reported by 74.1% of respondents, followed by difficulties in technology integration due to data heterogeneity (55.6%) and a lack of professional talent (55.6%) [6] - The technology requirements for trusted data spaces show a clear hierarchy, with identity authentication and access management being the most critical technology at 77.8%, followed by data interoperability and privacy computing at 66.7% [9] Group 3: Deployment Methods and Cost Expectations - The preferred deployment method for trusted data spaces is SaaS, favored by 63.0% of respondents, as it addresses the high resource and cost challenges effectively [8] - Over 65% of small and medium-sized enterprises prefer using government-provided or leading enterprise-led trusted data spaces, while larger enterprises show a higher inclination towards self-built private deployments [12] Group 4: Future Trends and Development Recommendations - Recommendations for future development include strengthening ecosystem collaboration among government, leading enterprises, and data infrastructure providers to explore innovative business models [14] - Accelerating core technology evolution is essential, with a focus on lightweight architecture and AI integration to support high concurrency and intelligent applications [14]