What exactly is a data asset? Understand data asset and data element management in one article!

In August 2023, the Ministry of Finance issued a notice on the "Interim Provisions on Accounting Treatment of Enterprise Data Resources", which introduced the concept of data asset inclusion in the financial statements, which is one of the sources of data assets.

In the "20 Data Articles" released in December 2022, the basic system of data was proposed - opinions on building a data basic system to better play the role of data elements, involving four basic systems of data: property rights system, transaction system, distribution system, and governance system, and defining data property rights.

The concept of the three rights of data, namely the right to hold data resources, the right to process and use data, and the right to operate data products, was innovatively proposed in the "20 Articles of Data". At present, the three rights of data are similar to the newly established land property rights system in 1988 mentioned above, which is still in its early stages. There is a hundred schools of thought in the industry, and a unified view has not yet been proposed.

What is a data asset?

According to the national standard document GB/T40685-2021 "Requirements for Data Asset Management of Information Technology Services", "data assets" refer to legally owned or controlled data resources that can be measured and bring economic and social value to organizations, with characteristics such as value-added, shareable, controllable, and quantifiable.

What are data elements?

Data elements refer to data resources that participate in social production and business activities, exist in electronic form, and play important value through computational methods. It is a core component of the digital economy, alongside traditional production factors such as land, labor, and capital, and has become an important force in promoting high-quality economic development

According to calculations by CITIC Securities, the size of China's data factor market is expected to reach a new level of 200 billion yuan by 2025 and exceed one trillion yuan by 2030. With policy support, enterprise participation, and market demand release, the processes of data processing, registration, and listing are expected to be further improved, promoting data openness and sharing, injecting more vitality into the intelligent transformation of enterprises and the high-quality development of the digital economy.

According to the National Data Resource Survey Report (2023), the total data production in China reached 32.85ZB in 2023, a year-on-year increase of 22.44%. Strengthening data asset management has become an important task in order to better leverage the scale advantage of China's massive data.

How do enterprises manage their data assets?

Data assets need to be extracted from raw data. Enterprises generate a large amount of data in their daily production and operation processes, such as consumer browsing and purchasing data, industrial machine production and operation data, vehicle environment perception and decision-making data, product logistics location data, medical records and inspection report data, etc.

The data volume is large, the types are diverse, and the value density is low. It needs to be processed to further play the functions of supporting analysis, reasoning, calculation, and decision-making, thus forming data assets.

According to the "2023-2024 China Data Asset Development Research Report" jointly released by the China Academy of Electronic Information Industry Development and the Blockchain Research Institute, the market-oriented path of data assets mainly includes four stages: data resource utilization, data productization, data assetization, and data capitalization.

● Data Resource Utilization: Through processes such as data collection, organization, rating, and aggregation, disordered and chaotic raw data is transformed into organized and valuable data resources.

●Data productization: Starting from customer scenarios and business applications, using computing power and algorithms to process data resources into data products, such as data visualization, big data application platforms, etc.

● Data assetization: Guided by expanding the economic benefits and application empowerment of data, through value evaluation, efficient operation, and other methods, data products can achieve internal application, sharing and openness, circulation and trading, and promote the realization of data value.

●Data capitalization: Based on the consensus of data asset returns and values, endow data with financial attributes, empower the completion of data trust enhancement, data pledge financing, data asset securitization, data valuation and equity investment, data trust, etc., so that the economic value of data can be recognized by the financial market.

Effective data asset management requires four major abilities

The core significance of the "one strategy" for enterprise data asset operation and management lies in its close focus on data as a core element, aiming to effectively aggregate data providers, developers, consumers, managers, and decision-makers to form a collaborative ecosystem.

Regarding the external provision of data assets, four core competencies need to be built: data integration capability, governance capability, asset planning and development capability, and asset service operation capability. Firstly, integrate data resources to improve data quality; Secondly, conduct asset inventory and develop customized data products; Finally, build a data operation platform similar to e-commerce to facilitate consumers' access. Internally, data interfaces need to be improved to ensure smooth flow. These measures collectively promote the maximization of the value of data assets.

DCMM Data Management Capability Maturity Assessment Model

Enterprise Data Asset Management Path Planning