  To satisfy the need for analytical data in the development of digital
services, many organizations use data warehouse, and, more recently, data lake
architectures. These architectures have traditionally been accompanied by
centralized organizational models, where a single team or department has been
responsible for gathering, transforming, and giving access to analytical data.
However, such centralized models presuppose stability and are incompatible with
agile software development where applications and databases are continuously
updated. To achieve more agile forms of data management, some organizations
have therefore begun to experiment with distributed data management models such
as 'data meshes'. Research on this topic is however limited. In this paper, we
report findings from a case study of a public sector organization in Norway
that has begun the transition from centralized to distributed data management,
outlining both the benefits and challenges of a distributed approach.
