T/GDIIA 006.09-2024 Active Group standards

T/GDIIA 006.09-2024 Data Governance Part 9: Specification for Acceptance Evaluation Services of Data Governance Projects

Publish Date: 2024-05-06 Implement Date: 2024-05-06 For services related to genuine standard inquiry, procurement, translation, and other related services in China, please Contact Us

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Basic Information

Standard Code: T/GDIIA 006.09-2024

Standard Type: Group standards

Standard Status: Active

is_force_gb: no

CCS Name: Information processing technology

ICS Name: Comprehensive Application of Information Technology

Publish Date: 2024-05-06

Implement Date: 2024-05-06

Pages: 13 pages

Scope

Scope: This standard sets forth the evaluation basis, overall process, phase division, and work content and specific requirements for the acceptance evaluation of data governance projects. This standard is applicable to third-party evaluation service organizations conducting acceptance evaluations of data governance projects. Main technical content: This standard proposes the evaluation basis, overall process, phase division, and work content and specific requirements for the acceptance evaluation of data governance projects. The formulation of this standard aims to standardize the acceptance evaluation of data governance projects and address the following issues: a) Standardization of project acceptance: It provides a standardized acceptance process and evaluation method for data governance projects, ensuring that the projects are conducted in accordance with established quality standards and requirements. It also provides guidance and service norms for third-party evaluation service organizations to carry out acceptance evaluations of data governance projects. b) Data governance quality evaluation: Through a standardized evaluation process, the quality of data governance projects can be systematically evaluated, including aspects such as data governance organizational structure, systems, technical solutions, data quality, and data security. c) Risk identification and management: During the evaluation process, problems and potential risks in the project are identified, and improvement suggestions are put forward to help the project team take timely measures to reduce risks. d) Continuous improvement: By analyzing the evaluation results, the project implementation team is encouraged to formulate and implement improvement plans, promoting the continuous optimization of data governance projects. e) Effect evaluation: The effectiveness of data governance projects is evaluated, including user satisfaction and business value, providing quantified feedback for