Published: 27 March 2024
数据中台的热度在持续几年后，已然消散。本研究分析了数据中台热度下降的原因，以及后数据中台时代里市场的演变，有助于数据和分析领导者重新构想数据和分析（D&A）战略以及运营实践。
随着企业将焦点从中心化数据管理和复用性逐渐转向追求数据变现，数据中台（DMO）已经跟不上发展步伐。
部署数据中台会产生高昂的成本，同时，也为在增长放缓的整体经济环境中证明数据和分析（D&A）投资的价值合理性带来了挑战。
数据中台的中心化运营模式难以满足迅速变化的需求，因此需要一个适应性的D&A运营模式，在治理之下扩展数据全民化。
生成式人工智能（GenAI）等新兴技术的出现，有望增强下一代数据中台的能力，赋能更多的AI原生消费者。
运用产品管理实践，与财务和业务运营等主要利益相关者密切合作，建立一个全面的数据治理机制作为数据资产管理的基础。
采用价值流映射方法，利用技术平台的嵌入式价值优化功能，推动有关技术文化和素养的项目，从而优先实现D&A投资的业务价值。
采用混合D&A架构，在实施域级分析的同时，确保良好的治理和可观测性。
以某一个供应商或生态系统解决方案为起点，快速从大语言模型（LLM）赋能的D&A功能中获益，解决数据环境的集成复杂性和治理难题。
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