Field parameters in Power BI provide a dynamic way to customize and control aspects of data modeling and report visualization. They enable users to alter data inputs or visual properties without altering the underlying data model, enhancing flexibility and interactivity. By creating parameterized fields, users can change filtering conditions, measure calculations, or even data sources on-the-fly, streamlining the exploration process.
This feature empowers data analysts to swiftly adapt their analyses to evolving requirements, thus fostering agile decision-making. Field parameters not only enhance user experience but also facilitate the creation of more responsive and adaptable Power BI reports, ultimately enabling more insightful and impactful data-driven insights.
How to do it - Data Preparation
Field Parameter accepts fully qualified Columns and measures. For this sample we created two measures.r accepts fully qualified Columns and measures. For this sample we created two measures.
Total Profit = SUM( Financials[Profit] ) & Total Discount = SUM( Financials[Discount] )
Total Profit, calculates the sum of the Profit column in the Financials table and Total Discount, calculates the sum of the Discounts column in the Financials table.
Stage 1 - Create the Field Parameter
Go to Modelling > New Parameter > Fields
By Vicente A Juan Magallanes - 9th August 2023 - fp20 analytics
Stage 2 - Select the measures or columns for your parameter
Go to Modelling > New Parameter > Fields > Select Measures
Stage 3 - Prepare your Chart
Go to Charts Visualization > Enter your X-axis > Enter your Parameter measure
Stage 4 - Your Chart is ready!!
Pick a Measure in the chart with the slicer.
Conclusion - The Avantages of Field Parameters
The advantages of using a field parameter to input two measures and creating a filter for both measures in a single chart are:
Flexibility and Customization: With a parameter, users can customize and dynamically change the measures they want to compare in real-time, providing greater flexibility and adaptability in data analysis.
Comparative Analysis: By creating a filter for both measures in a single chart, users can easily perform comparative analysis between two key metrics, enabling them to identify relevant correlations and trends.