Published: 25 March 2024
在中国，许多企业机构仍将成本削减视为数据和分析（D&A）领域云采用的主要动机，却忽视了敏捷性、安全性等其他价值主张。中国的数据和分析领导者可以利用本报告评估其D&A云旅程，并设定一个更全面的价值主张。
2022年底Gartner数据和分析云采用情况调研发现，82%的中国受访者选择在公有云上部署数据和分析（D&A）项目的主要动机是为了“削减数据运营成本”。
近半数的中国受访者计划在2025年前在其D&A云合作策略中完全采用来自云服务提供商的原生方案，较2022年有此计划的受访者数量翻了一倍。
由于复杂的D&A环境和沉重的技术债务，中国的企业机构要在公有云上运营D&A资产，需要花费大量成本。现有的的云上成本管理（FinOps）解决方案/实践并不能充分解决这一问题。
在2022年底，只有5%的中国受访者表示，他们的隐私和法务/网络安全部门的利益相关者参与了人工智能和分析领域的供应商选型流程。在其他国家的受访者中，这一比例（28%）要高出许多。
从总拥有成本（TCO）角度计算D&A云部署的成本，不仅包括软件和基础设施的购买成本，还要考虑部署、集成、培训、管理、维护和升级方面的支出。
平衡供应商锁定风险和集成维护成本，选择合适的D&A供应商合作策略。参考Gartner专门针对中国市场的报告，比如有关D&A的市场指南，以跟踪本地市场和供应商的动态。
优先选择完全托管型D&A云服务，不仅仅基于成本因素，还应基于业务敏捷性和新技术等其他价值主张。采用FinOps思维和主动元数据等方法，量化D&A公有云部署的业务价值。
在选择人工智能（AI）和分析领域的云服务供应商时，应让业务线、合规和安全等非D&A部门也参与进来。这种协作有助于在部门之间对人工智能和分析上云的价值和风险达成共识，特别是在早期概念验证（POC）阶段。
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Analysts:
Xingyu Gu, Feng Gao, Carolin Zhou
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