How to Optimize Your Power BI Report Performance with DAX

Introduction

The performance of your Power BI reports is crucial for delivering an optimal user experience. In this article, we'll explore the DAX optimization techniques that our experts use daily at Datakhi.

1. Understanding the DAX Calculation Engine

The DAX engine uses two main components:

• The formula engine: Evaluates DAX expressions
• The storage engine: Retrieves data from the model

To optimize your reports, you need to minimize the work of these two components.

2. DAX Best Practices

Avoid Calculated Columns When Possible

Calculated columns are evaluated during refresh and stored in memory. Prefer measures when the context allows:

// Calculated column (to avoid)
Margin = [Sales] - [Costs]

// Measure (recommended)
Margin = SUM(Sales[Amount]) - SUM(Costs[Amount])

Use Function Parameters

Some functions have optional parameters that will optimize your measures:

// Poor performance
Margin =
    IF(
        [Turnover] - [SupplierPurchasePrice] = 0,
        0,
        [Turnover] / ([Sales] - [SupplierPurchasePrice])
    )

// Better performance
Margin =
    DIVIDE(
        [Turnover],
        [Sales] - [SupplierPurchasePrice],
        0
    )

3. Optimize the Data Model

• Remove unnecessary columns: Each column consumes memory
• Use appropriate data types: An integer is lighter than a decimal
• Avoid high cardinality columns: They increase model size

4. Use Performance Analyzer

Power BI Desktop includes a Performance Analyzer tool that allows you to identify the slowest visuals. Enable it via the "View" tab.

Conclusion

DAX optimization is an art that comes with experience. At Datakhi, our certified Power BI consultants help companies audit and optimize their reports.

Need an audit of your Power BI reports? Contact us to discuss your needs.