How to Overcome the Top 3 Data Flow Challenges and Secure Your Data Assets

Data as an Asset: Challenges in Data Flow

The road to data circulation is complex. According to the national data standards committee, data element flow involves policies and regulations, circulation systems, models, technologies, and standards, forming the overall framework.

Policy and Regulation

Policies and laws provide the foundation for standardized data product transactions and ownership, leading to data circulation systems such as data ownership, assessment, circulation, and supervision. Once established, market‑driven operations create circulation models including registration, pricing, sharing, and service operation.

Technology

Underlying technologies like blockchain and privacy‑preserving computation enable "data usable but not visible," breaking ownership constraints and driving data trade.

Three Major Challenges in Data Flow

Data Security : Rapid data growth raises risks of leakage, tampering, and loss during transmission, storage, and use, requiring encryption, de‑identification, and backup.

Compliance of Data Flow Activities : Multiple parties and stages demand compliance in data collection, processing, analysis, usage, and cross‑industry, cross‑border exchanges.

Security of Data Flow Infrastructure : Protecting hardware, software, and network components of data flow facilities is essential.

Five Measures to Address Data Security Challenges

Improve Legal and Regulatory Framework : Establish comprehensive data security laws and regulations to guide protection and supervision.

Enhance Data Security Technologies : Develop and apply encryption, de‑identification, backup, and other techniques to safeguard data.

Build a Data Security Protection System : Implement policies, technologies, and management practices for multi‑layered protection.

Strengthen Training and Education : Raise awareness among data flow participants to reduce incidents.

Promote International Cooperation : Collaborate globally to create standards for cross‑border data security.

Six‑Step Method for Data Asset Entry into Financial Statements

Identify Data Assets : Catalog internal and external data that qualify as assets.

Meet Asset Definition : Demonstrate ownership or control and expected economic benefits.

Determine Measurement Method : Choose appropriate accounting methods such as cost, depreciation, or fair value.

Formulate Accounting Policies : Define procedures for initial recognition, subsequent measurement, impairment testing, and derecognition.

Prepare Financial Statements : Incorporate data assets into balance sheets, income statements, and cash‑flow statements as required.

Disclose Relevant Information : Reveal asset categories, quantities, values, sources, and impact on performance for transparency.

Why Various Roles in the Data Element Industry Chain Should Record Data Assets

Clarify Data Ownership : Distinguish ownership, processing, and product rights to facilitate transactions.

Promote Data Circulation and Trading : Establish mechanisms for internal and external data exchange.

Allocate Benefits Fairly : Follow the principle of "who invests, who contributes, who benefits".

Strengthen Data Security Governance : Build robust security management to prevent leaks and misuse.

Enhance Valuation and Financing : Enable accurate asset valuation to attract investment.

Drive Digital Economy Development : Leverage data assets for innovation, efficiency, and high‑quality growth.

In summary, recording data assets transforms data resources into commercial value, improves financial transparency, supports financing, and propels the entire data‑driven economy forward.