How can you be flexible and promptly give people the data they need, but do so in a way that is sustainable and doesn’t create potential governance or compliance issues? This can be a difficult scenario for central teams to manage as they seek to balance user enablement with risk mitigation. It’s common for business users to request new data in upstream data sources so that they can answer new problems. Enriching or combining centrally managed Power BI datasetsīusiness data needs are constantly evolving as the business strategy adapts to change. In this article, we explore how this challenge is typically addressed, and how composite models can be an appealing solution. Another challenge for these central datasets is incorporating new data. For example, central teams should train users to improve their data literacy and monitor what content is created and how it’s being used. However, this model also requires additional effort for governance. Business users consume these datasets from Power BI desktop, Excel, or other analytics workloads in Fabric (like notebooks, which are fantastic, by the way) to address business problems with data.Ī managed self-service BI model presents several advantages, including fewer requests for the central BI team and a preserved truth in re-usable shared datasets. In this model, a Center of Excellence (COE) or central team of data professionals create and manage Power BI datasets. For example, organizations can opt for a managed self-service BI model (instead of a centralized enterprise BI model). Power BI provides a variety of ways to enable users with self-service analytics.
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