[Ben Ray]

Power BI provides basic analytics features and supports Python and R for advanced analytics, but these require external tools or coding expertise. Clients often expect seamless advanced analytics without additional dependencies, which can be hard to deliver natively in Power BI. Power BI consultant must set up external environments, which increases project complexity and costs. Additionally, non-technical end-users may find it challenging to maintain such solutions. Power BI’s reliance on third-party tools for advanced analytics limits its usability for clients needing sophisticated statistical models, predictive analytics, or machine learning insights.

[Ben Ray]

Power BI lacks built-in version control or multi-user editing, making collaboration cumbersome for development teams. Simultaneous editing of dashboards or reports is not supported, leading to potential bottlenecks in larger teams. Developers often resort to third-party tools like Git for version control, adding complexity to the workflow. The absence of features like change tracking or rollback increases the risk of errors during updates. These collaboration limitations are particularly challenging for projects requiring frequent iterations, reducing overall efficiency and potentially delaying delivery timelines for large-scale Power BI development initiatives.

[Autor]

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