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 concept that includes architectural aspects to promote data democratization and enables organizations to become truly data-driven. 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, best practices, 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 industry experts 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 concept of a data product model. In our work, we derive multiple best practices and suggest organizations embrace elements of data fabric, 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 best practices 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 guidelines for the successful adoption of data mesh.

翻译：随着数据和人工智能的重要性日益提升，各组织正努力实现更加数据驱动的运营。然而，当前的数据架构未必能跟上数据与分析用例的规模与范围。实际上，现有架构往往无法交付其承诺的价值。数据网格是一种包含架构层面的社会技术概念，旨在促进数据民主化，使组织能够真正实现数据驱动。由于数据网格概念尚属新兴，缺乏来自实践领域的经验性洞察。具体而言，关于引入数据网格的驱动因素、相关挑战、最佳实践、业务影响及潜在原型模式的理解仍存在空白。为填补这一空白，我们与行业专家进行了15次半结构化访谈。研究结果显示，行业专家在向与数据网格概念相关的联邦式治理转型、数据产品开发、供应与维护责任的转移，以及数据产品模型概念方面面临困难。本研究提炼出多项最佳实践，建议组织采纳数据编织的要素、监控数据产品使用情况、在早期阶段创造速赢成果，并组建优先关注数据产品的小型专注团队。我们承认组织需根据自身需求应用最佳实践，同时推导出两种提供更详细建议的原型模式。研究发现综合了行业专家的洞察，为研究人员和实践者提供了成功采用数据网格的指南。