With the increasing importance of data and artificial intelligence, organizations strive to become more data-driven. However, current data architectures are not necessarily designed to keep up with the scale and scope of data and analytics use cases. In fact, existing architectures often fail to deliver the promised value associated with them. Data mesh is a socio-technical, decentralized, distributed concept for enterprise data management. As the concept of data mesh is still novel, it lacks empirical insights from the field. Specifically, an understanding of the motivational factors for introducing data mesh, the associated challenges, implementation strategies, its business impact, and potential archetypes is missing. To address this gap, we conduct 15 semi-structured interviews with industry experts. Our results show, among other insights, that organizations have difficulties with the transition toward federated governance associated with the data mesh concept, the shift of responsibility for the development, provision, and maintenance of data products, and the comprehension of the overall concept. In our work, we derive multiple implementation strategies and suggest organizations introduce a cross-domain steering unit, observe the data product usage, create quick wins in the early phases, and favor small dedicated teams that prioritize data products. While we acknowledge that organizations need to apply implementation strategies according to their individual needs, we also deduct two archetypes that provide suggestions in more detail. Our findings synthesize insights from industry experts and provide researchers and professionals with preliminary guidelines for the successful adoption of data mesh.

翻译：随着数据和人工智能日益重要，企业努力向数据驱动转型。然而，当前的数据架构未必能够应对数据与分析用例在规模和范围上的扩展需求。事实上，现有架构往往无法实现其承诺的预期价值。数据网格是一种面向企业数据管理的社会技术性、去中心化、分布式概念。由于数据网格概念尚属新颖，业界缺乏来自实际应用的实证洞察，特别是关于引入数据网格的动机因素、相关挑战、实施策略、业务影响及潜在原型模式的认识仍存在空白。为弥补这一不足，我们开展了15次半结构化专家访谈。研究结果显示，企业在向数据网格概念所对应的联邦治理模式过渡、数据产品开发/提供/维护的责任转移，以及整体概念理解方面面临困难。基于研究，我们归纳出多种实施策略，建议企业建立跨域指导单元、监控数据产品使用情况、在早期阶段创造速赢效果，并优先组建专注数据产品的小型专业团队。虽然我们承认企业需要根据自身需求选择实施策略，但进一步提炼出两种原型模式以提供更具体的建议。本研究综合了行业专家的洞察，为研究人员和从业者成功采纳数据网格提供了初步指导框架。