Unpacking data democratization - how communities of practice help organizations develop and scale their data practices

Hippolyte Lefebvre & Christine Legner

European Journal of Information Systems2026https://doi.org/10.1080/0960085x.2025.2607450article
AJG 4ABDC A*
Weight
0.50

Abstract

Data democratization, the empowerment of a wide range of employees to engage with data, has become a strategic priority for organizations aiming to create value from data. Existing studies focus on removing organizational or technical barriers to accessing and using data, but offer limited insight into how data democratization materializes in practice. We draw on the concept of communities of practice (CoPs) to examine how data practices are developed and scaled within organizations to meaningfully integrate data and domain knowledge. From an analysis of 45 communities at 21 companies, we identify three types of CoPs that foster data democratization: (1) CoPs that embed data into work practices, (2) CoPs that develop data practices around tools and methods, and (3) CoPs that foster collective data awareness. These CoPs interact through distinct boundary interactions that stimulate practice exchange across the organization. We theorize three enablers that facilitate their interactions: the embeddedness of spanners-in-practice, the malleability of boundary objects, and the supportive governance structures. This study advances information systems research and the emerging field of data studies by unpacking how cross-functional learning and collaboration enable data democratization. For practitioners, we offer guidance for orchestrating and nurturing CoPs to foster data-driven value creation.

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https://doi.org/https://doi.org/10.1080/0960085x.2025.2607450

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@article{hippolyte2026,
  title        = {{Unpacking data democratization - how communities of practice help organizations develop and scale their data practices}},
  author       = {Hippolyte Lefebvre & Christine Legner},
  journal      = {European Journal of Information Systems},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1080/0960085x.2025.2607450},
}

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Unpacking data democratization - how communities of practice help organizations develop and scale their data practices

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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