If two reports disagree on revenue, the cause usually sits underneath the charts.
Your reports run slowly, totals don’t match, and adding one new measure takes a developer. These problems usually trace back to the data model, the engine behind every Power BI report.
We design star schema data models, a simple layout with one main table joined to smaller lookup tables. Then we write DAX measures that work out your business metrics correctly, from simple totals to time comparisons, dynamic segments and what-if analysis.
Star schema models built to run fast
Custom DAX measures for complex business metrics
Time comparisons such as year over year, month to date and rolling averages
What-if analysis, with inputs your team can adjust
We map your databases, APIs, Excel files and cloud services, then use Power Query to pull in and shape the data.
We arrange that data into a star schema, with clear links set between tables.
We write DAX measures for your metrics, from running totals to cohort analysis, which tracks groups of customers over time.
We cut table sizes, tighten measures and set up incremental refresh, so large datasets stay fast.
We’ve built Power BI solutions for a range of organizations. Every report depends on its data model, so that is where we put the most care.
DAX (Data Analysis Expressions) is Power BI’s formula language. It handles metrics that drag-and-drop can’t express, such as year-over-year growth, running totals and weighted averages.
Yes. Slow reports usually point to data model issues. We put a proper star schema in place, cut table sizes, tune DAX measures and set up incremental refresh, which reloads only new data.
Yes. With proper DAX measures, Power BI handles cohort analysis, customer lifetime value, funnel analysis and other advanced metrics. The key is a data model built to support them.
We build data models that combine databases, APIs, Excel files and cloud services. Power Query pulls in and reshapes the data, and links in the model tie it all together.
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