Industrial Industry

Lack of Unified Data Standards

The data registration and inventory process lacks unified data standards, which fails to effectively prevent issues such as data confusion, conflicts, multiple sources for the same data, and diversity in data types.

Chaotic Data Cycle Planning

Chaotic data cycle planning/inability to achieve data monitoring during the planting and sales processes prevents historical data and experience from being accumulated into methods to guide production.

Difficulty in Coordinating Business Management

There is confusion in managing permissions for data addition, deletion, modification, and usage, making it difficult to establish a single, comprehensive, accurate, and complete data view that reflects the enterprise's operational status.

Uneven Data Quality

Data quality issues such as data redundancy, missing data, and data conflicts cannot be promptly identified and effectively resolved.

Security Oversight Is Imperative

The lack of an effective data security management mechanism and inadequate control over access to sensitive, private, and confidential information results in challenges in data masking and decryption (de-identification and decryption) compliance, potentially posing reputational and legal risks to enterprises.

Difficulty in Assessing Data Value

The data evaluation system and data assetization are currently in their nascent stages. Issues related to data appreciation, preservation, and valuation need urgent attention, and the monetization of data assets remains a long and arduous task.