Migrating Power BI Dashboards to Metabase

Goal

The primary goal was to migrate existing dashboards from Power BI to Metabase while preserving their analytical intent and improving usability. Power BI had become a bottleneck: dashboards loaded slowly, filtering large datasets caused performance issues, and available visualizations did not fully support the client’s reporting needs.

The client had attempted to handle the migration internally but could not achieve the desired outcome. They needed an external team to accurately rebuild the dashboards in Metabase, rethink visual choices where needed, and ensure the final solution was reliable and easy to use for business stakeholders.

An additional complexity was that we worked through a consulting intermediary rather than directly with the end client, and database access was limited to Metabase only. This required careful planning, clear assumptions, and close coordination throughout the project.

Result

We rebuilt three key dashboards in Metabase, focusing on performance, clarity, and practical usability.

The client’s data is stored across Google Sheets and Microsoft SQL Server, with Metabase serving as the primary interface for querying and visualization. Because direct database access was not provided, all SQL development, exploration, and validation were performed within Metabase. While this limited the speed of certain iterations, it ensured alignment with the production environment.

Rather than copying dashboards one-to-one, we improved their structure: introduced tab-based layouts, applied filters strategically to avoid loading entire datasets at once, and selected visualizations better suited to the underlying business questions. These changes significantly improved responsiveness and reduced cognitive load for users.

Delivered dashboards included:

• Sales Dashboard: sales performance broken down by customers, sales teams, and individual sales reps, with flexible filtering.

• Store-Specific Dashboard: performance by store type (e.g. wholesale vs retail) with product category breakdowns.

• Financial Dashboard: revenue, costs, profitability, and margin analysis in a structured, executive-friendly layout.

As a result, dashboards no longer freeze under large data volumes, load times are predictable, and users can focus on analysis rather than tooling limitations.