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智能化数据管理知识体系指南

作译者：国际数据管理协会大中华区

出版时间：2026-07 千字数：856 版次：01-01 页数：504

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目 录
第 1 章 智能化数据管理体系总览····················································································.1
1.1 引言·················································································································.1
1.1.1 数据管理基本概念回顾 ················································································.1
1.1.2 数据管理核心原则再审视 ·············································································.2
1.2 《DAMA 数据管理知识体系指南》总括 ···································································.3
1.3 DMBOK 数据管理框架回顾及推广情况 ····································································.4
1.3.1 DMBOK 数据管理框架回顾 ··········································································.4
1.3.2 DMBOK 推广情况 ······················································································.6
1.4 现有数据管理模式存在的问题 ················································································.9
1.4.1 业务适配滞后：数据管理与业务发展不同步 ·····················································.9
1.4.2 体系运转低效：数据管理流程复杂且依赖人工··················································.11
1.4.3 人才支撑薄弱：数据业务综合人才“一将难求”··················································.11
1.4.4 智能技术不足：传统数据管理缺少动态调整 ····················································.12
1.5 智能化数据管理模式 ···························································································.13
1.5.1 智能化驱动的数据治理特征 ·········································································.13
1.5.2 业务导向的智能数据架构设计 ······································································.13
1.5.3 跨域融合的智能数据中枢构建 ······································································.15
1.5.4 智能技术支撑的业务价值实现 ······································································.16
1.5.5 实践路径导向的未来趋势演进 ······································································.18
1.6 智能化数据管理的原则 ························································································.19
1.6.1 目标导向：针对合适的场景使用 AI································································.19
1.6.2 赋能增效：AI 并非替代而是提升效率·····························································.19
1.6.3 流程内嵌：将 AI 能力注入数据管理全生命周期活动··········································.20
1.6.4 协同作战：AI 人才与数据管理专家协同工作····················································.20
1.6.5 质量筑基：AI 应用需保障数据质量 ·······························································.20
1.7 智能化数据管理活动 ···························································································.21
1.7.1 企业数据管理活动规划（P）········································································.21
1.7.2 智能化数据管理应用场景识别（P）·······························································.21
1.7.3 数据管理智能化模型开发（D） ····································································.22
1.7.4 数据管理智能化模型集成部署与应用（D） ·····················································.22
1.7.5 数据管理智能化模型应用效果评价与验证（O） ···············································.23
1.7.6 数据管理智能化应用的控制机制建立（C） ·····················································.23
1.7.7 数据管理智能化应用的优化与改进（O） ························································.24
1.8 智能化数据管理框架简介 ·····················································································.24
1.9 智能化数据管理成果度量指标 ···············································································.28
1.9.1 数据管理效率提升 ·····················································································.28
1.9.2 周期压缩 ·································································································.29
1.9.3 人员依赖减少 ···························································································.29
第 2 章 建章立制智能化 ·······························································································.30
2.1 引言················································································································.30
2.2 目标和原则·······································································································.31
2.2.1 核心目标 ·································································································.31
2.2.2 实施原则 ·································································································.32
2.3 业务驱动因素····································································································.33
2.4 输入················································································································.33
2.4.1 标准文档模板 ···························································································.33
2.4.2 内容输入 ·································································································.36
2.5 活动················································································································.36
2.5.1 制度流程规划 ···························································································.36
2.5.2 制度流程建设 ···························································································.40
2.5.3 制度流程运营 ···························································································.42
2.6 交付成果··········································································································.43
2.6.1 建章立制智能体 ························································································.43
2.6.2 角色参考清单 ···························································································.43
2.6.3 制度流程参考清单 ·····················································································.44
2.6.4 知识库 ····································································································.46
2.6.5 提示词模板 ······························································································.46
2.6.6 训练后的大模型 ························································································.49
2.6.7 制度运营方案 ···························································································.50
2.7 方法················································································································.51
2.7.1 SIPOC 模型······························································································.51
2.7.2 文档生命周期管理 ·····················································································.51
2.8 技术工具··········································································································.52
2.8.1 大模型：智能化的核心引擎 ·········································································.52
2.8.2 智能体：流程自动化的执行载体 ···································································.53
2.8.3 制度平台：制度和知识管理的核心载体 ··························································.54
2.8.4 RPA：重复性工作助手················································································.55
2.9 评估指标··········································································································.56
2.9.1 效率提升 ·································································································.56
2.9.2 制度流程质量提升 ·····················································································.56
2.9.3 成本降低 ·································································································.57
2.10 实施指南 ········································································································.57
2.10.1 制度流程挖掘··························································································.57
2.10.2 制度流程智能化推荐·················································································.58
2.10.3 基于智能体的制度流程评审········································································.59
第 3 章 数据标准智能化 ·······························································································.60
3.1 引言················································································································.60
3.1.1 数据标准管理面临的挑战 ············································································.60
3.1.2 数据标准智能化概述 ··················································································.61
3.2 数据标准内涵与智能化演进 ··················································································.62
3.2.1 数据标准定义与核心构成 ············································································.62
3.2.2 数据标准、数据质量与元数据的关系 ·····························································.63
3.2.3 从传统管理到智能化管理的演进 ···································································.63
3.3 业务驱动因素····································································································.64
3.4 目标和原则·······································································································.65
3.4.1 目标 ·······································································································.65
3.4.2 原则 ·······································································································.66
3.5 输入················································································································.67
3.5.1 外部标准输入 ···························································································.67
3.5.2 内部资产输入 ···························································································.67
3.5.3 管理要点 ·································································································.69
3.6 活动················································································································.69
3.6.1 现状评估与规划制定 ··················································································.69
3.6.2 数据标准制定 ···························································································.71
3.6.3 收集并整理输入材料 ··················································································.72
3.6.4 数据字典补全及标准符合性检核 ···································································.73
3.6.5 构建组织级数据标准知识库和知识图谱 ··························································.73
3.6.6 训练数据标准智能模型 ···············································································.74
3.6.7 开展标准冲突检测与自动修复，实现存量数据字典标准化···································.74
3.6.8 设计数据标准运营流程，验证效果并迭代优化··················································.75
3.7 输出················································································································.76
3.7.1 完整且质量有保障的数据字典 ······································································.76
3.7.2 业务术语清单 ···························································································.77
3.7.3 组织级数据标准清单 ··················································································.77
3.7.4 组织内部数据标准知识库和知识图谱 ·····························································.77
3.7.5 组织内部数据标准智能模型及推荐引擎 ··························································.77
3.7.6 存量和增量数据标准应用流程 ······································································.78
3.7.7 标准落标率、冲突修复率等监控报表与持续改进机制·········································.78
3.8 技术工具··········································································································.78
3.8.1 数据标准管理平台 ·····················································································.79
3.8.2 智能化辅助工具 ························································································.79
3.8.3 标准化应用监控与可视化工具 ······································································.80
3.9 方法················································································································.81
3.9.1 PDCA 方法 ······························································································.81
3.9.2 标准分级管理办法 ·····················································································.81
3.10 度量指标 ········································································································.82
3.10.1 数据标准制定效率提升程度········································································.82
3.10.2 数据标准质量情况····················································································.83
3.10.3 数据标准化率提升情况··············································································.84
3.10.4 冲突检测与修复的准确率···········································································.84
3.10.5 推荐结果的采用率····················································································.85
3.10.6 人工依赖程度下降比例··············································································.85
3.11 实施指南·········································································································.85
3.11.1 实施路径：四阶段演进路线········································································.85
3.11.2 组织保障与协同机制·················································································.88
3.11.3 技术实施关键考量····················································································.88
3.11.4 变革管理与文化推广·················································································.89
3.11.5 持续运营与价值度量·················································································.89
3.11.6 关键成功要素··························································································.90
第 4 章 数据架构智能化 ·······························································································.91
4.1 引言················································································································.91
4.1.1 数据架构简史 ···························································································.92
4.1.2 智能化时代的核心挑战 ···············································································.94
4.1.3 数据架构智能化概述 ··················································································.94
4.2 业务驱动因素····································································································.96
4.3 目标和原则·······································································································.96
4.3.1 核心目标 ·································································································.97
4.3.2 核心原则 ·································································································.97
4.4 输入················································································································.98
4.4.1 企业数据架构现况·······················································································.98
4.4.2 业务架构 ·································································································.99
4.4.3 业务需求 ·································································································.99
4.5 活动················································································································.99
4.5.1 评估现有数据架构规范 ···············································································100
4.5.2 制定路线图 ······························································································100
4.5.3 管理项目内的企业需求 ···············································································102
4.5.4 与企业架构集成 ························································································104
4.5.5 数据架构智能运维 ·····················································································104
4.6 方法················································································································105
4.6.1 智能元数据分类分级方法 ············································································105
4.6.2 智能数据架构优化建议生成方法 ···································································107
4.7 度量指标··········································································································110
4.7.1 架构智能化过程指标 ··················································································110
4.7.2 架构输出结果指标 ·····················································································110
4.7.3 横向集成支持指标 ·····················································································111
4.7.4 纵向项目约束指标 ·····················································································111
4.7.5 业务价值指标 ···························································································112
4.8 实施指南··········································································································112
4.8.1 实施原则 ·································································································113
4.8.2 实施建议 ·································································································113
4.8.3 实施效果 ·································································································114
第 5 章 数据建模智能化 ·······························································································115
5.1 引言················································································································115
5.1.1 传统数据建模面临的挑战与痛点 ···································································116
5.1.2 业务场景复杂化带来的新挑战 ······································································117
5.2 基本概念与术语·································································································118
5.2.1 数据建模领域的基本概念 ············································································118
5.2.2 数据建模智能化的相关概念 ·········································································123
5.3 业务驱动因素····································································································124
5.3.1 效率与质量双提升需求 ···············································································124
5.3.2 知识管理与复用机制构建需求 ······································································125
5.3.3 合规要求内嵌需求 ·····················································································126
5.4 目标和原则·······································································································126
5.4.1 目标 ·······································································································126
5.4.2 智能化建模实施原则 ··················································································127
5.5 输入················································································································128
5.5.1 基础输入 ·································································································128
5.5.2 智能化支撑输入 ························································································130
5.6 活动················································································································131
5.6.1 规划数据建模 ···························································································131
5.6.2 建立数据模型 ···························································································132
5.6.3 审核数据模型 ···························································································134
5.6.4 维护数据模型 ···························································································135
5.7 输出················································································································136
5.7.1 数据模型输出 ···························································································136
5.7.2 智能化分析输出 ························································································137
5.7.3 配套支撑输出 ···························································································138
5.8 技术工具··········································································································139
5.8.1 数据建模与可视化工具 ···············································································139
5.8.2 数据处理与集成工具 ··················································································140
5.8.3 质量管控与运维工具 ··················································································141
5.8.4 知识管理工具 ···························································································141
5.9 方法················································································································142
5.9.1 业务驱动方法 ···························································································142
5.9.2 分层建模方法 ···························································································142
5.9.3 知识图谱辅助方法 ·····················································································143
5.9.4 人机协同方法 ···························································································143
5.9.5 持续学习与优化方法 ··················································································143
5.10 度量指标 ········································································································143
5.10.1 效率与质量提升指标················································································144
5.10.2 复用与扩展性指标····················································································145
5.10.3 合规与风险管控指标·················································································146
5.11 实施指南·········································································································147
5.11.1 实施策略与准备·······················································································148
5.11.2 实施路线图：分阶段推进···········································································148
5.11.3 核心场景落地指引····················································································149
场景一：智能化的需求分析与转化 ·········································································149
场景二：自动化落标与命名规范 ············································································150
场景三：存量模型逆向智能化重构 ·········································································150
5.11.4 常见挑战与应对策略·················································································151
第 6 章 元数据管理智能化 ····························································································152
6.1 引言················································································································152
6.2 基本概念与术语·································································································153
6.2.1 元数据（Metadata） ···················································································153
6.2.2 元数据管理/治理 ·······················································································154
6.2.3 数据血缘（Data Lineage） ···········································································155
6.2.4 数据目录（Data Catalog）············································································156
6.2.5 智能化元数据管理 ·····················································································158
6.2.6 元模型 ····································································································159
6.3 业务驱动因素····································································································161
6.4 与组织目标对齐的元数据管理智能化战略制定 ··························································162
6.5 目标和原则·······································································································163
6.5.1 目标 ·······································································································163
6.5.2 原则 ·······································································································163
6.5.3 小结 ·······································································································164
6.6 元数据管理·······································································································164
6.6.1 识别元数据管理需求 ··················································································164
6.6.2 建立元数据标准化与治理机制 ······································································166
6.6.3 智能元数据采集与分类 ···············································································169
6.6.4 元数据架构设计 ························································································172
6.6.5 智能运营 ·································································································176
6.7 技术工具··········································································································181
6.7.1 元数据管理平台 ························································································181
6.7.2 搜索引擎与智能标签系统 ············································································182
6.7.3 图数据库与血缘分析工具 ············································································182
6.7.4 数据集成工具与消息队列 ············································································183
6.7.5 API 网关、数据虚拟化工具与 AI/ML 平台·······················································184
6.8 方法················································································································185
6.8.1 元数据采集框架 ························································································185
6.8.2 数据血缘构建算法 ·····················································································185
6.8.3 智能分类打标模型 ·····················································································186
6.8.4 质量规则引擎 ···························································································186
6.8.5 语义相似度计算 ························································································186
6.8.6 图谱关系推理 ···························································································187
6.8.7 变更影响分析模型 ·····················································································187
6.8.8 自动元数据补全 ························································································187
6.8.9 异常检测算法 ···························································································188
6.8.10 推荐系统方法··························································································188
6.9 度量指标··········································································································188
6.9.1 度量指标体系建设目标 ···············································································188
6.9.2 建设原则 ·································································································189
6.9.3 验收标准设计 ···························································································189
6.9.4 AI 规则嵌入与智能化度量 ···········································································190
6.9.5 运维与持续改进 ························································································191
6.9.6 与国家及行业标准的对标 ············································································192
6.9.7 小结与建议 ······························································································192
6.10 实施指南 ········································································································193
6.10.1 云环境下元数据管理·················································································193
6.10.2 协同治理································································································194
6.10.3 行业实践——政务领域智能检索系统····························································194
第 7 章 数据质量管理智能化 ·························································································196
7.1 引言················································································································196
7.1.1 数据质量管理面临的挑战 ············································································196
7.1.2 数据质量管理智能化概述 ············································································196
7.2 业务驱动因素····································································································198
7.3 目标和原则·······································································································198
7.3.1 目标 ·······································································································198
7.3.2 原则 ·······································································································199
7.4 输入················································································································200
7.4.1 战略与目标维度 ························································································200
7.4.2 业务规则基准维度 ·····················································································201
7.4.3 技术基准维度 ···························································································201
7.4.4 知识与经验维度 ························································································202
7.5 活动················································································································203
7.5.1 基于智能化技术的数据质量定义 ···································································203
7.5.2 基于智能化技术的数据质量度量评估 ·····························································203
7.5.3 基于根因分析的数据质量问题分析 ································································204
7.5.4 基于辅助工具的数据质量问题优化与改善 ·······················································205
7.5.5 智能化质量监测控制 ··················································································208
7.6 输出················································································································209
7.6.1 数据质量定义 ···························································································210
7.6.2 数据质量度量评估 ·····················································································210
7.6.3 数据质量问题分析 ·····················································································211
7.6.4 数据质量问题优化 ·····················································································212
7.6.5 数据质量监测控制 ·····················································································213
7.7 技术工具··········································································································213
7.7.1 数据血缘/链路图谱工具 ··············································································213
7.7.2 数据质量智能核查工具 ···············································································214
7.7.3 数据质量监测工具 ·····················································································214
7.7.4 数据质量工单管理工具 ···············································································214
7.7.5 数据质量辅助治理工具 ···············································································214
7.7.6 数据/元数据质量知识库 ··············································································214
7.7.7 数据质量审计报告生成工具 ·········································································215
7.7.8 Agent 指令数据集 ······················································································215
7.7.9 数据质量管理智能体 ··················································································215
7.7.10 智能化数据标注工具·················································································215
7.8 方法················································································································216
7.8.1 数据质量规则识别与生成方法 ······································································216
7.8.2 数据质量问题溯源分析方法 ·········································································216
7.8.3 基于指标体系的数据质量评价测算方法 ··························································216
7.8.4 业务数据智能补全与治理方法 ······································································216
7.8.5 人工智能算法训练数据增强方法 ···································································217
7.8.6 智能化数据标注方法 ··················································································217
7.8.7 智能体 Prompt 工程常用方法·······································································217
7.8.8 高质量数据集构建及优化方法 ······································································218
7.9 度量指标··········································································································219
7.9.1 效益评估指标 ···························································································219
7.9.2 质量水平指标 ···························································································220
7.9.3 质量趋势指标 ···························································································221
7.9.4 数据问题管理指标 ·····················································································221
7.9.5 其他指标 ·································································································221
7.10 实施指南 ········································································································222
7.10.1 数据质量实施规划····················································································222
7.10.2 数据质量设计··························································································223
7.10.3 数据质量执行··························································································224
7.10.4 数据质量监控与优化·················································································225
7.10.5 实施风险与应对·······················································································226
第 8 章 主数据与参考数据智能化···················································································227
8.1 引言················································································································227
8.1.1 传统主数据与参考数据管理的现实挑战 ··························································227
8.1.2 大模型技术演进赋能主数据管理 ···································································228
8.1.3 主数据与参考数据管理语境关系图 ································································229
8.2 业务驱动因素····································································································230
8.2.1 业务敏捷性 ······························································································230
8.2.2 成本优化 ·································································································231
8.2.3 价值变现 ·································································································231
8.2.4 风险控制 ·································································································232
8.3 目标和原则·······································································································232
8.3.1 目标 ·······································································································233
8.3.2 原则 ·······································································································234
8.4 输入················································································································236
8.4.1 业务数据输入 ···························································································236
8.4.2 元数据输入 ······························································································237
8.4.3 知识与标准输入 ························································································238
8.4.4 业务规则输入 ···························································································239
8.4.5 技术能力输入 ···························································································240
8.5 活动················································································································240
8.5.1 智能规划活动 ···························································································240
8.5.2 智能标准制定活动 ·····················································································241
8.5.3 智能数据处理活动 ·····················································································242
8.5.4 智能分发与图谱构建活动 ············································································243
8.5.5 智能质量与安全活动 ··················································································244
8.5.6 智能生命周期管理活动 ···············································································244
8.5.7 智能保障活动 ···························································································245
8.6 输出················································································································246
8.6.1 智能数据资产 ···························································································246
8.6.2 治理模型资产 ···························································································248
8.6.3 运营与服务资产 ························································································248
8.7 技术工具··········································································································249
8.7.1 技术工具演进路径 ·····················································································249
8.7.2 技术工具逻辑架构 ·····················································································250
8.7.3 关键使能技术 ···························································································252
8.7.4 工具类型 ·································································································255
8.8 方法················································································································256
8.8.1 认知构建方法 ···························································································257
8.8.2 执行编排方法 ···························································································258
8.8.3 进化运营方法 ···························································································259
8.9 度量指标··········································································································260
8.9.1 生产与资产指标 ························································································260
8.9.2 业务价值与服务指标 ··················································································261
8.9.3 进化能力与运营指标 ··················································································262
8.10 实施指南 ········································································································263
8.10.1 辅助增强期·····························································································263
8.10.2 原生融合期·····························································································264
8.10.3 自治进化期·····························································································265
8.10.4 挑战与风险应对策略·················································································267
第 9 章 非结构化数据管理智能化···················································································269
9.1 引言················································································································269
9.2 业务驱动··········································································································270
9.2.1 传统非结构化数据管理痛点 ·········································································270
9.2.2 智能化带来的变革 ·····················································································272
9.3 目标················································································································273
9.3.1 降本增效，简化流程 ··················································································273
9.3.2 高效采集，严控质量 ··················································································273
9.3.3 安全合规，主动防控 ··················································································274
9.3.4 实时洞察，赋能业务 ··················································································274
9.3.5 法规保留，电子存证 ··················································································274
9.4 输入················································································································275
9.4.1 数据源 ····································································································275
9.4.2 技术输入 ·································································································276
9.4.3 治理输入 ·································································································276
9.5 非结构化数据加工处理 ························································································277
9.5.1 清洗：提升数据质量与一致性 ······································································277
9.5.2 标注：赋予数据语义与结构 ·········································································278
9.5.3 增强：提升数据多样性与鲁棒性 ···································································278
9.5.4 合成：生成高质量虚拟数据 ·········································································279
9.5.5 加工处理流程整合与自动化 ·········································································279
9.6 非结构化数据用途 ······························································································279
9.6.1 智能检索：从关键词到语义理解 ···································································279
9.6.2 知识管理：从数据到知识图谱 ······································································280
9.6.3 高质量数据集：支撑 AI 模型训练··································································281
9.7 非结构化数据管理 ······························································································282
9.7.1 质量智能分析与推荐 ··················································································282
9.7.2 安全合规 ·································································································283
9.7.3 标准智能检查 ···························································································284
9.8 交付成果··········································································································285
9.8.1 训练数据：非结构化数据管理的“燃料”···························································285
9.8.2 算法模型：非结构化数据管理的“智能引擎”·····················································285
9.8.3 工具平台：非结构化数据管理的“操作系统”·····················································285
9.9 技术工具··········································································································286
9.9.1 自然语言处理 ···························································································286
9.9.2 大模型 ····································································································286
9.9.3 智能体 ····································································································286
9.9.4 非结构化数据管理智能化平台 ······································································287
9.10 方法 ··············································································································287
9.10.1 全生命周期管理·······················································································287
9.10.2 嵌入 AI 项目建设 ·····················································································287
9.10.3 固化业务规则的知识工程···········································································288
9.10.4 建立持续优化机制····················································································288
9.10.5 借鉴智能化最佳实践·················································································289
9.11 评估指标·········································································································289
9.11.1 效率指标································································································289
9.11.2 质量指标································································································291
9.11.3 成本指标································································································291
9.11.4 业务价值指标··························································································293
第 10 章 数据安全管理智能化 ·······················································································294
10.1 引言 ··············································································································294
10.1.1 数据安全管理面临的挑战···········································································294
10.1.2 数据安全管理智能化概述···········································································295
10.2 业务驱动因素 ··································································································296
10.2.1 降低风险：从合规底线到系统性防控····························································296
10.2.2 促进业务增长：从效率保障到价值赋能·························································297
10.2.3 安全能力资产化：从成本中心到战略支点······················································297
10.3 目标和原则 ·····································································································297
10.3.1 目标······································································································298
10.3.2 原则······································································································298
10.4 输入 ··············································································································299
10.4.1 战略与合规维度·······················································································299
10.4.2 资产与特征维度·······················································································299
10.4.3 架构与环境维度·······················································································300
10.5 活动 ··············································································································300
10.5.1 识别数据安全需求····················································································300
10.5.2 制定数据安全制度····················································································303
10.5.3 数据智能发现与分类分级···········································································304
10.5.4 数据安全架构设计与实施···········································································307
10.5.5 智能安全管理运营····················································································311
10.6 输出 ··············································································································312
10.6.1 资产与策略类输出····················································································313
10.6.2 技术与防御类输出····················································································313
10.6.3 运营与合规类输出····················································································313
10.7 技术工具 ········································································································314
10.7.1 基础管理技术··························································································314
10.7.2 智能化工具·····························································································317
10.8 方法 ··············································································································324
10.8.1 智能/元数据驱动的数据分类分级方法 ···························································324
10.8.2 应用 CRUD 矩阵的数据安全需求识别方法 ·····················································325
10.8.3 基于动态基线的风险管控方法·····································································325
10.8.4 零信任安全架构实施方法···········································································326
10.8.5 隐私计算技术应用方法··············································································326
10.8.6 数据安全成熟度评估（DSMM）实施方法······················································327
10.8.7 自动化合规检查方法·················································································327
10.9 度量指标 ········································································································328
10.9.1 风险管理与合规指标·················································································328
10.9.2 组织与流程指标·······················································································329
10.9.3 智能化成熟度指标····················································································329
10.10 实施指南·······································································································330
10.10.1 数据生命周期全过程安全 ·········································································330
10.10.2 云环境安全 ···························································································332
10.10.3 AI 数据安全 ··························································································332
10.10.4 供应链数据安全 ·····················································································333
10.10.5 可信数据空间 ························································································334
第 11 章 数据仓库与商务智能化 ····················································································335
11.1 引言···············································································································335
11.2 业务驱动·········································································································337
11.2.1 决策效率提升需求····················································································337
11.2.2 多源异构数据整合需求··············································································337
11.2.3 数据价值深度挖掘需求··············································································338
11.2.4 成本优化核心诉求····················································································338
11.3 目标原则·········································································································338
11.3.1 核心目标································································································339
11.3.2 实施原则································································································339
11.4 输入···············································································································340
11.4.1 业务需求信息··························································································340
11.4.2 AI 相关专项输入······················································································341
11.4.3 前序章节智能化成果输入···········································································341
11.4.4 技术环境信息··························································································342
11.5 活动···············································································································342
11.5.1 规划阶段：AI 驱动的需求与架构设计 ···························································342
11.5.2 控制阶段：全流程质量、合规与风险管控 ······················································346
11.5.3 开发阶段：AI 赋能数据仓库开发 ·································································348
11.5.4 运营阶段：商务智能服务与数据产品维护 ······················································350
11.6 输出···············································································································352
11.6.1 数据仓库系统与应用交付物········································································352
11.6.2 AI 智能化能力成果···················································································353
11.6.3 安全与合规保障成果·················································································354
11.7 方法···············································································································355
11.7.1 需求－架构双落地法·················································································355
11.7.2 全流程质量与风险闭环管控法·····································································356
11.7.3 数据集成－建模－ETL 全链路智能开发法······················································357
11.7.4 运维－产品适配－业务协同全周期保障法 ······················································357
11.8 智能化技术工具································································································358
11.8.1 核心 AI 与大模型工具 ···············································································358
11.8.2 非结构化数据处理工具··············································································359
11.8.3 数据建模与元数据工具··············································································359
11.8.4 数据质量工具··························································································360
11.8.5 监控与分析工具·······················································································360
11.8.6 架构适配工具··························································································360
11.8.7 运维与支撑工具·······················································································361
11.9 度量指标·········································································································361
11.9.1 效率类指标·····························································································361
11.9.2 质量类指标·····························································································362
11.9.3 成本类指标·····························································································363
11.9.4 合规类指标·····························································································364
11.10 实践指南 ·······································································································365
11.10.1 传统应急指挥运维的瓶颈 ·········································································365
11.10.2 场景建设核心难点 ··················································································365
11.10.3 数据仓库+BI+智能化技术三维赋能 ·····························································366
11.10.4 评价指标 ······························································································368
第 12 章 数据资产管理智能化 ·······················································································369
12.1 引言 ··············································································································369
12.2 基本概念与术语································································································370
12.3 业务驱动 ········································································································371
12.3.1 数据资产流通需求与协同需求·····································································371
12.3.2 数据资产价值实现需求··············································································371
12.3.3 数据资产资本化需求·················································································372
12.3.4 智能化管理升级需求·················································································373
12.3.5 风险与合规平衡需求·················································································373
12.4 目标 ··············································································································374
12.4.1 业务目标································································································374
12.4.2 技术能力目标··························································································375
12.4.3 价值目标································································································376
12.5 输入 ··············································································································377
12.5.1 数据输入································································································377
12.5.2 业务输入································································································378
12.5.3 约束输入································································································378
12.6 活动 ··············································································································379
12.6.1 智能获取································································································379
12.6.2 智能盘点与治理·······················································································380
12.6.3 智能审核································································································382
12.6.4 智能应用与运营·······················································································384
12.7 输出 ··············································································································387
12.7.1 策略与机制输出·······················································································387
12.7.2 模板与方法输出·······················································································387
12.7.3 报告与交付成果·······················································································388
12.8 方法 ··············································································································388
12.8.1 RACI 责任矩阵方法··················································································388
12.8.2 全生命周期管理方法·················································································389
12.8.3 AI 驱动的智能化管理方法··········································································389
12.8.4 数据中台集成方法····················································································389
12.8.5 价值评估与运营方法·················································································389
12.9 技术工具 ········································································································390
12.9.1 建模与管理工具·······················································································390
12.9.2 处理与运营工具·······················································································391
12.9.3 安全与合规工具·······················································································393
12.10 评估指标·······································································································394
12.10.1 资产效果指标 ························································································394
12.10.2 合规与智能指标 ·····················································································395
12.11 实施指南 ·······································································································396
12.11.1 实践起点：现状调研与保障机制·································································396
12.11.2 实践原则：数据资产管理粒度划分原则························································397
12.11.3 实施路线：分阶段推进资产化进程······························································398
12.11.4 实施过程：建立持续运营与改进机制···························································399
第 13 章 大数据与数据科学智能化 ·················································································400
13.1 引言 ··············································································································400
13.2 业务驱动 ········································································································401
13.2.1 战略与市场需求·······················································································401
13.2.2 能力提升需求··························································································402
13.2.3 成本降低需求··························································································403
13.2.4 数据普惠化需求·······················································································403
13.3 目标 ··············································································································403
13.3.1 业务目标································································································403
13.3.2 技术目标································································································404
13.3.3 价值目标································································································405
13.4 输入 ··············································································································405
13.4.1 数据输入································································································405
13.4.2 业务输入································································································406
13.4.3 行业知识与领域标准·················································································407
13.5 活动 ··············································································································408
13.5.1 数据战略与需求转化·················································································408
13.5.2 数据理解与采集·······················································································409
13.5.3 数据预处理与特征工程··············································································409
13.5.4 建模与算法选型·······················································································410
13.5.5 模型评估与迭代优化·················································································411
13.5.6 模型部署与智能运维·················································································412
13.5.7 数据闭环与反馈升级·················································································413
13.5.8 智能化工具的推广与运营···········································································413
13.6 输出 ··············································································································413
13.6.1 分析报告类输出·······················································································414
13.6.2 数据产品输出··························································································415
13.6.3 优化策略类输出·······················································································417
13.7 技术工具 ········································································································418
13.7.1 数据全生命周期工具·················································································419
13.7.2 模型与生成式 AI 工具 ···············································································421
13.7.3 AI 数据分析与建模工具 ············································································421
13.7.4 运维与工程化工具····················································································422
13.8 评估指标 ········································································································423
13.8.1 数据能力评估··························································································423
13.8.2 智能效果评估··························································································424
13.8.3 效率与用户体验·······················································································425
13.8.4 技术与运维·····························································································426
13.8.5 普惠与可持续··························································································426
13.9 实施指南 ········································································································427
13.9.1 大数据方向实践·······················································································427
13.9.2 数据科学方向实践····················································································429
第 14 章 数据管理成熟度评估智能化··············································································432
14.1 智能化评估的动因与范式重塑··············································································433
14.1.1 核心业务需求驱动····················································································433
14.1.2 技术与方法演进驱动·················································································435
14.1.3 关键问题解决导向····················································································436
14.2 智能化评估的核心目标·······················································································437
14.2.1 过程优化目标··························································································438
14.2.2 结果提升目标··························································································439
14.2.3 业务赋能目标··························································································440
14.3 智能化评估的输入要素·······················································································440
14.3.1 多维评估模型体系····················································································441
14.3.2 全域多模态数据输入·················································································442
14.3.3 标准、规则与知识库·················································································443
14.4 智能化评估的核心活动与流程··············································································444
14.4.1 评估框架构建活动····················································································444
14.4.2 智能化评估全流程····················································································446
14.4.3 典型应用场景··························································································448
14.5 智能化评估的产出与价值····················································································450
14.5.1 框架与模型资产输出（核心资产层）····························································451
14.5.2 流程与报告输出（应用交付层）··································································452
14.5.3 业务与技术价值沉淀（价值沉淀层）····························································453
14.6 关键技术工具与平台··························································································454
14.6.1 评估管理平台：指挥中心···········································································454
14.6.2 自动化数据采集连接器：神经网络·······························································455
14.6.3 智能分析引擎：智慧大脑···········································································457
14.6.4 可视化与交互仪表盘：价值呈现··································································459
14.7 核心方法与算法································································································460
14.7.1 基于规则的模式匹配方法···········································································461
14.7.2 基于 NLP 的文档分析方法··········································································462
14.7.3 基于知识图谱的关联分析方法·····································································463
14.7.4 基于机器学习的预测与推荐方法··································································464
14.7.5 智能化评估理论方法·················································································465
14.8 智能化评估的效能度量指标·················································································466
14.8.1 过程效能指标··························································································467
14.8.2 结果质量指标··························································································469
14.8.3 业务价值指标··························································································470
14.8.4 智能能力指标··························································································471
14.9 实施保障体系 ··································································································472
14.9.1 组织保障与变革管理·················································································473
14.9.2 评估系统的治理与风控··············································································475
14.9.3 AI 伦理：算法公平性、结果可解释性与申诉机制 ···········································477
14.9.4 系统鲁棒性：抵御攻击与异常处理能力·························································477

序一
数据管理正迎来关系数据库诞生四十多年来最深刻的一次变革。
纵观数据管理的发展历程，每一次重大技术进步——从数据仓库、商业智能，到云计算、大数据、数据湖，再到数据网格和数据产品——都不断提升了数据的规模、处理速度和应用价值。然而，在这些技术浪潮中，数据管理的核心理念和实践方式却始终没有发生根本性的改变。数据专业人员依然主要依靠人工和各类工具，完成数据建模、元数据管理、数据治理、数据质量、数据安全、数据架构等工作。
人工智能（Artificial Intelligence，AI）的出现，彻底改变了这一局面。
AI 第一次不再只是数据管理的辅助工具，而开始成为数据管理工作的参与者，甚至是协作者。AI 能够理解业务语言，发现数据模式，识别数据关系，自动生成元数据，推荐治理策略，识别敏感数据，检测数据质量问题，生成文档，甚至能够与数据管理人员共同设计、建设和运营现代数据体系。过去需要数周甚至数月才能完成的工作，如今可能只需几分钟；许多过去根本无法完成的任务，也正在变为现实。
正是基于这一深刻变化，本书应运而生。本书的核心观点十分简单，却具有深远意义：
AI 不仅是一项需要数据管理来支撑的新技术，它正在重新定义数据管理这门学科本身。近年来，关于"如何管理 AI 所需的数据"（Data Management for AI）已经有大量研究和实践。为了训练机器学习模型和大语言模型，越来越多的组织开始加强数据治理、数据质量、数据工程和数据基础设施建设。这些工作无疑十分重要，但它们仅仅回答了 AI 与数据管理关系中的一半问题。另一半，也是本书重点探讨的问题，则是：在 AI 时代，我们应该如何进行数据管理（AI-based Data Management）？这一问题要求我们重新审视数据管理几乎所有的知识领域。
当 AI 能够自动构建业务术语库时，元数据管理将如何演进？当基础模型能够从海量数据中自动发现业务规则时，数据质量管理将发生哪些变化？当智能体（Agent）能够持续监测数据合规性、自动执行治理流程并协调问题整改时，企业的数据治理模式又将如何重构？当 AI 成为数据管理团队中的"数字同事"而不仅仅是一个工具时，数据管理人员又需要具备哪些新的能力？
这些早已不是未来的设想，而是正在全球范围内不断发生的现实。
大语言模型（LLM）、智能体（Agent）、检索增强生成（RAG）、多模态 AI 以及智能自动化等技术的快速发展，正在重新定义数据管理工作的成本结构、组织方式和能力边界。许多过去高度依赖人工经验和重复劳动的工作，正在变得更加智能、更具规模、更加高效。
与此同时，AI 也带来了许多全新的挑战，例如模型治理、AI 生成数据、合成数据、提示词管理、知识增强、可信 AI、可解释性、伦理治理以及 AI 自身的治理等。这意味着，数据管理已经不再局限于传统意义上的数据，而正在逐步扩展成为人与 AI 共同管理企业知识、共同创造业务价值的新型管理体系。
然而，这种变革并没有削弱传统数据管理的重要性。
恰恰相反，AI 时代比以往任何时候都更加依赖高质量的数据管理。
越来越多的组织已经认识到，AI 能够产生多大的价值，最终取决于它能够获取怎样的数据，以及能够信任怎样的知识。元数据混乱，AI 便无法正确理解业务；治理机制缺失，AI 自动化就难以可信运行；数据质量低下，再先进的大模型也无法产生可靠的结果。
AI 既能够放大数据管理的优秀实践，也会放大数据管理中的缺陷。
因此，数据质量、数据治理、数据架构、元数据管理、数据安全、数据隐私以及数据生命周期管理等传统数据管理原则，不仅没有过时，反而成为智能时代不可替代的基础。
真正发生改变的，是这些原则的实现方式。
过去依靠人工维护元数据，如今 AI 可以持续自动发现和维护；过去依赖周期性的质量检查，如今 AI 能够实现实时监测和预测性修复；过去依赖人工执行治理流程，如今智能体能够自动执行治理策略、协调业务流程；过去的数据目录，正在演进成为融合元数据、本体、业务知识和 AI 推理能力的企业知识系统（Enterprise Knowledge System）。
本书正是围绕这些变化展开。
本书并非试图否定过去几十年来形成的数据管理理论，而是在继承经典数据管理思想的基础上，引入 AI 时代新的方法论、技术体系、架构模式和最佳实践。本书重新审视数据管理各个知识领域，探讨 AI 能够如何赋能数据管理，以及如何安全、可信、可持续地将 AI 融入数据管理全过程。
本书并非试图预测未来，而是希望为正在经历这一巨大变革的数据管理专业人士提供一份切实可行的实践指南。
我相信，未来的数据管理人员，将越来越少地从事重复性的文档编写和人工维护工作，而更多地承担知识验证、业务判断、治理设计和战略决策等高价值工作。他们将管理的不仅仅是数据系统，更是人与 AI 共同组成的新型工作体系；他们协调的不仅仅是数据流程，更是人类智慧与机器智能之间的协同。
本书面向所有关注数据管理未来发展的读者，包括首席数据官（CDO）、数据治理负责人、数据架构师、数据工程师、数据分析师、数据管理员、AI 从业者、企业数字化管理者，以及高等院校教师和有志于进入数据管理领域的学生。
我同样希望，本书能够为整个数据管理学科的发展贡献新的思考。
每一个时代都会继承前人的知识，也都会面对新的技术革命。今天，AI 正在挑战许多长期以来形成的理念和实践，但与此同时，它也为数据管理带来了前所未有的发展机遇。通过积极而理性地拥抱 AI，我们有机会推动数据管理从"管理数据"迈向"管理知识"，从支撑业务运行迈向驱动智能决策，从一项专业技术能力发展成为企业核心竞争力的重要组成部分。
未来的数据管理，不属于人类，也不属于 AI。
未来的数据管理，属于人与 AI 的协同。
而这一新的时代，已经到来。
最后以汪广盛先生希望我写的一句话来结束这个序言：谨以此书，献给所有正在推动数据管理迈向智能时代的实践者、研究者和创新者。
皮特.艾肯 
2026 年 7 月 15 日
于美国弗吉尼亚州
智能化数据管理知识体系指南

序二
在数字化时代，企业战略就是数字化战略，企业数据资产的总和，便是企业的价值。特别是伴随机器学习的普及，数据不仅仅要服务于人，更要服务于智能体，对数据管理的要求由此进入了一个新的时代。我们有很多问题似是而非，没有共识，比如数字化和信息化的定义，数字化时代的本体的定义、数据治理、数据的四化等。以郑博士为代表的国际数据管理协会大中华区的很多专家均从事数字技术研究多年，基于他们的实践和研究成果，完成了这部著作。试图去解答上述问题，并就技术发展和实践的路径给出一个理论框架。我们之间的讨论使我深感他们的独到见解值得与大家分享。大模型正在激发我们对未来的无限想象，但，如果没有高质量的数据，也就是我们常说的规模化、标准化、特征化、关联化的数据，我们将一事无成。无论是将人类已知的知识普及化，将人类的隐形知识显性化，还是探索人类未知的领域，都需要我们做好数据治理工作。希望本书的工作对读者有所启发，并形成共识。
 神州数码董事局主席

序三
数据管理是一项系统性工程，涉及组织、架构、制度、流程、工具、人员、价值等诸多因素。其复杂度高、基础性强、周期长，对主要负责人和参与人员的专业能力都有着很高的要求。近年来，在监管驱动、政策引导、企业内需和智能化浪潮等多重因素的推动下，越来越多的政府和企业开始着手构建符合自身实际的数据管理体系。在这个过程中，许多数据管理从业者认真研读了《DAMA数据管理知识体系指南》，从中掌握了系统的数据管理知识与技能，并以此作为理论指导，逐步推进企业级的数据管理工作。该书陪伴并见证了行业的成长，也让我们始终心怀敬意与感激。
不过，受制于大量历史遗留问题，数据管理工作普遍存在效率不高、周期偏长的情况。数据管理的效率和能力，与业务和管理对数据应用的要求之间，始终存在着一定的矛盾。尤其在当下人工智能技术迅猛发展的背景下，这一矛盾愈发凸显——传统的数据管理方式，已经越来越难以满足 AI智能体对高质量数据的使用要求。与此同时，数据作为新型生产要素，其价值释放对数据管理的质量与效率提出了前所未有的高要求。如何破解这一矛盾，成为摆在整个行业面前的一道“必答题”。
带着这样的思考，我邀请了业内九十多位资深的数据专家和 AI 专家，共同进行了多轮深入的探讨。大家普遍认为，将 AI 智能体引入数据管理工作，以此提升数据管理的效率，是完全可行的。基于这样的共识，我们开始了《智能化数据管理知识体系指南》一书的编写工作，希望通过数据专家与 AI 专家之间的思想碰撞和共同努力，借助 AI 智能体的引入，对现有数据管理的部分知识体系和工作模式进行优化，从而达到提升效率、降低对人员专业度和经验依赖的目的，在一定程度上缓解数据管理能力与业务需求之间的矛盾。更为重要的是，我们希望能够更好地适应 AI 智能体时代对数据管理提出的新要求——传统的数据管理，管理的对象和服务的对象都是人；而在 AI 智能体时代，我们既要兼顾人的需求，也要管好智能体、服务好智能体。这既是挑战，更是数据管理迈向新阶段的重要机遇。
本书以《DAMA 数据管理知识体系指南》修订版为基础，以引入 AI 智能体、推动传统数据管理领域的模式优化与效率提升为目标，并结合国内数据治理和数据管理的实践，构建了全书的结构和体系。全书共分为 14 章：第 1 章为智能化数据管理总览，以《DAMA 数据管理知识体系指南》修订版中的车轮图、语境关系图为参照，设计了智能化数据管理的车轮图及各领域的语境关系图，并提出了 AI 智能体引入后的效果评价指标；后续 13 章，均以智能化数据管理语境关系图为基本架构展开编写。同时，基于国内实际，本书增加了建章立制智能化、数据标准智能化、数据资产管理智能化三个章节——在国内的实际工作中，这三个部分通常作为独立且重要的领域来实施。这样的安排，既尊重了国际通行的知识框架，也回应了国内同仁在实际工作中的真实需要。为了验证 AI 智能体引入数据管理工作后的实际效果，我们在每章的最后部分，都提供了相关的实战案例，供读者参考和借鉴。
在阅读和使用的顺序上，建议读者可以先从第 1 章的总览入手，建立对智能化数据管理整体框架的认识，再结合自身的工作领域，选择相应的章节深入研读；章节末尾的案例，则可以帮助大家把书中的方法与自己的实际场景联系起来，边读边想，边想边用。我们也希望，这本书不仅是一份知识的整理，更能成为大家日常工作中顺手、好用的参考伙伴。
本书由九十多位作者共同完成，前后历时一年多。编写工作按照章节分为 14 个组，每组设一名组长，负责统筹与质量把控。在一年多的时间里，大家利用工作之余，反复讨论、数易其稿，字里行间凝聚着每一位参与者的心血。作为本书的总负责人，我深知其中的不易，在此衷心感谢各位组长和作者的参与和付出，尤其是各位组长，投入了大量的时间和精力。本书的 14 位组长（按章节顺序）分别是：郑保卫、赵耀军、袁小东、程川、刘晨、陈曦、邓志东、申镇、尹正、袁芳、张曦文、张森森、陈健璋、朱凯。
需要坦诚说明的是，书中涉及的许多方法和技术还处于理论探索阶段，实际效果尚未在实践中得到充分验证，如有不足之处，恳请各位读者多多谅解。同时，我们也真诚地欢迎各位读者积极参与进来，提出宝贵的意见和建议，与我们共同完善和提升这本书。数据管理的智能化之路才刚刚开始，需要全行业的同仁携手同行、共同探索。
最后，衷心祝愿每一位读者都能在阅读本书的过程中有所启发、有所收获，也期待与大家一同见证数据管理更加智能、更加高效的未来。
国际数据管理协会大中华区理事
恩核数据创始人
郑保卫

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