What are the difference between Implicit and Explicit measures in Power BI. Give an example of both types of measure

 In Power BI, implicit and explicit measures refer to different ways of defining and using measures (aggregated calculations) within a dataset. Here's how they differ:

1. Implicit Measures:

   • Implicit measures are automatically created by Power BI when you drag and drop a numeric field (e.g., sales amount, quantity sold) onto a visual.
   • Power BI automatically aggregates the numeric field using a default aggregation function (usually SUM) to create the implicit measure.
   • Implicit measures are created on-the-fly as you interact with the data in visuals, without the need for explicit definition.
   • They are convenient for quick analysis but may lack customization options.

   Example of an implicit measure:

   • You have a dataset with a "Sales Amount" field. When you drag and drop this field onto a bar chart, Power BI automatically creates an implicit measure that calculates the sum of sales amount for each category in the chart.

2. Explicit Measures:

   • Explicit measures are manually defined by users using DAX (Data Analysis Expressions) formulas within Power BI.
   • Users explicitly define the calculation logic and aggregation functions for explicit measures, providing more control and flexibility.
   • Explicit measures can incorporate complex calculations, conditions, and aggregations based on business requirements.

   Example of an explicit measure:

   • You define an explicit measure named "Total Profit" using the DAX formula: Total Profit = SUM(Sales[Sales Amount]) - SUM(Sales[Cost])
   • This explicit measure calculates the total profit by subtracting the total cost from the total sales amount.

Difference between Implicit and Explicit Measures:

• Creation: Implicit measures are automatically created by Power BI based on the fields dragged into visuals, while explicit measures are manually defined by users using DAX formulas.

• Flexibility: Implicit measures have limited flexibility as they are based on default aggregations, while explicit measures offer greater flexibility as users can define custom calculations and aggregations based on business logic.

• Control: Implicit measures are created on-the-fly by Power BI, whereas explicit measures provide users with full control over the calculation logic and aggregation functions.

In summary, implicit measures are automatically generated by Power BI for quick analysis, while explicit measures are manually defined by users for more complex and customized calculations. Both types of measures serve different purposes and can be used based on the specific requirements of the analysis.