Optimising Power BI query performance for high-volume operational reporting

Why star schema modelling outperforms flat tables

Many reporting teams import raw ERP extracts directly into Power BI as single wide denormalized tables. While simple initially, this approach severely degrades DAX evaluation performance once historical row counts exceed five million records.

Separating dimensions and facts

By re-architecting the data model into a clean star schema with dedicated surrogate keys, the VertiPaq engine achieves maximum dictionary compression ratios:

// Efficient measure with star schema
Total Sales Margin :=
DIVIDE(
    [Total Sales Amount] - [Total Product Cost],
    [Total Sales Amount],
    0
)

For industrial monitoring applications, keeping dimension tables narrow and fact tables numeric ensures sub-second visual refresh times even during peak shift reporting.