The year 2024 is heralded as a pivotal moment for China, being the designated "first year" for the marketization of data as a key factor in the nation's economic transformationAs the digital economy matures, the scale of China's data market is surging rapidlyAccording to statistics from the National Research Center for Cyber Security, the annual compound growth rate of the data market is projected to exceed 20%, with estimates indicating that by 2025, the data factor market could surpass 174.9 billion yuan (approximately $25 billion).

Industry insiders, during interviews, highlighted how the continuously improving policy environment has encouraged various entities to engage in the data factor marketMoreover, the rapid advancement of technologies such as privacy computing, big data analytics, and blockchain has further enhanced the efficiency and security of data circulationThese technological strides, paired with a favorable policy landscape, are key contributors to the swift expansion of the data trading ecosystem.

This rapid growth in data trading is highlighted not just by transaction scale, but also through a slew of governmental policies aimed at promoting the utilization and opening up of public data

Experts in the field agree that public data, which is typically abundant, high-quality, and laden with application potential, will unlock vast data value across various sectors, including urban governance and financial servicesHowever, as public data operation is still in its infancy, issues like unclear usage boundaries and an underdeveloped regulatory framework remain significant challenges that need to be addressed.

The activity within data trading is poised to escalate, as evidenced by the recent comprehensive guidelines issued by multiple national departments advocating for high-quality development in the data industry, wherein "data trading" is recognized as one of the top seven focal areas in data technology and industry development.

By the end of 2024, statistics from leading data exchanges indicate notable growth in trading volume across the nationFor instance, the Guiyang Big Data Exchange reported that as of December 24, 2024, it had accommodated 1,659 trading entities, registered 2,690 products, executed 4,039 data transactions, and accumulated a transaction value of 7.383 billion yuan

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Furthermore, projections for 2025 anticipate that Guiyang's data trading volume could reach 10 billion yuanThe Shanghai Data Exchange also reported a thriving trading environment, achieving a transaction volume exceeding 5 billion yuan with a catalog of over 5,000 products by the end of 2024. Excitingly, they expect that by 2025, the total value of data assets on their platform may also touch 10 billion yuan.

Wu Shenkua, a doctoral advisor at the Law School of Beijing Normal University and deputy director of the China Internet Association Research Center, explained that this surge in data trading activity can be attributed to several factorsFirst, a series of supportive policies deployed by both national and local governments have created a conducive environment for the development of the data factor marketAdditionally, technological advancements in privacy computing and blockchain have bolstered data security and circulation efficiency, fostering a healthy market expansion

Various industries are increasingly exploring data application possibilities, which is particularly evident in sectors such as intelligent manufacturing and financial services, giving rise to new business models and service forms.

The integration of data within the financial services domain is particularly intriguingTaking the case of Guiyang, organizations like Guiyang Big Data Exchange, along with Southern Electric Network and domestic data service provider Shuku Technology, have collaboratively developed a corporate marketing value assessment model based on electricity big dataBy combining electricity usage data with publicly available data, they constructed an evaluation index system for enterprises that enables more tailored loan strategies informed by a credit modelThis innovative approach integrates historical electricity consumption data, enhancing banks' abilities to deliver personalized lending services efficiently.

This potential for utilizing data in finance comes with its own set of challenges, according to Wu Shenkua

The foremost issue is data securitySafeguarding the integrity of data, especially that which encompasses significant amounts of personal privacy and commercial secrets, is of utmost importanceFurthermore, data quality and credibility pose additional hurdles, as financial institutions rely heavily on precise, high-quality data for risk assessment and decision-making processes, necessitating stringent verification and auditing protocols.

As the data factor market gathers momentum in 2024, the acceleration in public data utilization and circulation cannot be overlookedWhile prior attempts at regional public data initiatives had seen sluggish progress due to a lack of formal decrees, a flurry of public data-related policies officially rolled out in October 2024 has stimulated proactive exploration across several regions.

In terms of public data authorization models, Guizhou province serves as an exemplary case

As reported, public data operations in Guizhou are currently managed by the Provincial Big Data Bureau, which is responsible for guiding, coordinating, and scheduling the province's data circulation and trading management effortsThis initiative aims to nurture the data factor market and oversee the construction of a unified provincial data circulation trading platformGuizhou employs a tiered authorization approach—where the provincial and local government data supervisors grant licenses to operational entities—while also establishing a systematic mechanism for data operational authorization that clarifies roles, processes, and security management to unlock data value safely.

Separately, Zhang Sirui, an engineer at the China Academy of Information and Communications Technology, recently elaborated on three primary public data authorization models employed across the country

The first, a centralized one-to-one model, possesses authoritative power that maximizes the integrated value of data but may exhibit inefficiencies in adapting to market changesThe second model is a one-to-many approach by different operational units within various industries, which emphasizes specialization but increases coordination challengesThe last is a decentralized one-to-many model, which selectively matches operational entities based on scene-specific needs and distinct data characteristics, promoting a competitive market dynamic with its own management complexities.

With the launch of numerous supportive policies, many of the longstanding issues, such as the reluctance or hesitance to share public data, are gradually being mitigatedHowever, lingering uncertainties regarding data authorization and usage still existAs articulated by Wu Shenkua, following the recent standardization, localized initiatives are experimenting with varied authorization models, including granting direct authorizations to specific enterprises for commercial operations, as well as forming dedicated platforms for data operations

Such diverse explorations are bound to foster innovations in public services.

Nonetheless, Wu Shenkua also pointed out the existing data silos that persist between various departments, which hinder effective data integration and usageThe ambiguity surrounding data usage boundaries—particularly regarding what can be authorized for use and how citizens’ privacy is safeguarded—requires further delineationAdditionally, the regulatory framework is presently insufficient; a robust system for pre-approval, monitoring, and post-audit procedures is crucial to ensure lawful and compliant operationsWu Shenkua concludes that while significant progress has been made in the marketization of data factors, continuous optimization of policies, technological innovation, and market oversight are vital for advancing to a higher level of development.

From the interviews conducted, it is evident that some data operators are still unclear about their rights and responsibilities concerning their data assets