• Changes in metadata of the original system cannot be known about, making it difficult to make version control;

• Focus on the attributes of data dictionary without other types of attributes;

• Huge cost of data traceability, which is currently in the form of semi-automatic + manual entry of lineage information;

• Lack of data model design tools, and the difficulty of unifying the specifications at the development stage;

• Unsupport data desensitization and encryption;

• Lack of fine-grained permission control, such as for rows, columns, and cells.

• Lack of log and audit;

• No support for RBAC attribute-based permission control;

• Standard organizing is time consuming, difficult and in need of intelligent means to improve efficiency;

• Lack of existing industry data standards;

• The current data standards are more for ex post facto instead of ex ante control;

• Lack of product means for data standards consistency, which currently are mostly manual weak checks.

• Data standards cannot be automatically transformed into data quality rules checks;

• Lack of existing data quality rules;

• Lack of a closed-loop process for data quality improvement;