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Enterprise Data Strategy Board:2025年企业数据治理现状报告:体系现代化建设、组织难点破解及 AI 监管合规应对(英文版)(16页).pdf

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1、2025 STATE OFENTERPRISE DATAGOVERNANCEIn this report,we explore how senior data leaders aremodernizing governance programs,overcoming organizationalchallenges,and preparing for new demands like AI oversight.Introduction&MethodologyWe asked Enterprise Data Strategy Board members and other seniordata

2、leaders how they are structuring,scaling,and modernizing theirdata governance programs in 2025.Their insights reveal the evolvingpriorities,challenges,and strategies shaping governance across largeenterprises.We collected responses from 14 senior data leaders acrossapproximately eight industries.The

3、 survey concluded on April 18,2025,providing a timely snapshot of how organizations are advancinggovernance to meet todays demands.43%Healthcare/PharmaThe Data Leaders Represented In This SurveyMajority of survey respondents workHealthcare/Pharma or Finance industrieswith titles ranging from Directo

4、r to AVP ofdata governance,analytics,AI strategy,and technology.7%Insurance29%Finance7%Manufacturing7%Food&Beverage7%Technology2025 STATE OF ENTERPRISE DATA GOVERNANCE REPORTSURVEY PARTICIPANTSData Governance StructureResponses to this question show a nearlyeven divide between centralized andfederat

5、ed data governance models,eachchosen by 36%of respondents.Hybrid approaches are also gaining traction,cited by 29%,suggesting that manycompanies are experimenting with sharedownership models across business units.29%Hybrid Model36%CentralizedModel36%FederatedModel2025 STATE OF ENTERPRISE DATA GOVERN

6、ANCE REPORTSTRUCTUREWhat Matters Most in Data GovernanceWhen asked to rank the most importantaspects of governance,a majority of dataleaders put stewardship and ownership atthe top,followed closely by data qualityand metadata management.The results highlight a continued focus onaccountability,trust,

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1. **数据治理结构**:36%采用集中式,36%采用联邦式,29%采用混合模式。 2. **核心关注点**:数据治理中最重要的是数据管理职责(21%)和数据质量(19%)。 3. **成功关键**:33%认为需增加自动化,17%强调业务部门所有权。 4. **主要挑战**:28%难以量化ROI,22%遭遇业务团队抵触。 5. **KPI指标**:28%以数据质量为核心,但39%难以向领导层展示KPI价值。 6. **AI治理现状**:31%仍处于早期政策定义阶段,22%已建立AI专项框架。 7. **未来趋势**:未来5年将重点推进自动化、AI政策及文化转型。
**治理如何自动化?** **AI治理现状如何?** **数据质量如何衡量?**
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