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Show Data Point Based on Slicer Selection

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Hello readers, in this blog I will show, how to show the data points in a visual based on slicer selection.

Here is the view of the report,

In this view, all the values in the visual are from Sales table. Now, we want to have a slicer which has data points name and we want to show the selected data points in line visual.

Let’s get started…

Step 1: Create a slicer selection table using “Enter Data” feature.

Step 2: Create a slicer using “Selection” column from Slicer Selection table.

Step 3: Create measures for each data point. In this case, we have three data points i.e., Actuals, Forecast & Actuals PY.

Actuals TY = CALCULATE(SUM(Sales[Actual]),FILTER(Sales,CONTAINS(‘Slicer Selection’,’Slicer Selection'[Selection],”Actuals”)))

Forecast = CALCULATE(SUM(Sales[Forecast]),FILTER(Sales,CONTAINS(‘Slicer Selection’,’Slicer Selection'[Selection],”Forecast”)))

Actuals PY = CALCULATE([Previous Year Actual],FILTER(Sales,CONTAINS(‘Slicer Selection’,’Slicer Selection'[Selection],”Actuals PY”)))

Note: Keep the values parameter in CONTAINS same as in the “Selection” column’s value.

Step 4: Now, use the above measures in the visual

Now, you can select the data points you want to visualize from the Line Selection slicer on the top.

This is all about, showing the data points based on slicer selection.

I hope you will find this blog useful.

Gaurav Lakhotia
Data Analyst
Addend Analytics

Author By

Afroz Labbai

Afroz is a Data Engineer and Team Lead with 4+ years of experience in building scalable data platforms using Azure technologies such as Azure Data Factory, Azure SQL, Databricks, and Synapse. He specialises in ETL development, SQL optimisation, and data modelling, delivering reliable and cost-efficient solutions for enterprise analytics. He is passionate about continuous learning, mentoring teams, and driving data-driven decision-making.

Author By

Picture of Afroz Labbai

Afroz Labbai

Afroz is a Data Engineer and Team Lead with 4+ years of experience in building scalable data platforms using Azure technologies such as Azure Data Factory, Azure SQL, Databricks, and Synapse. He specialises in ETL development, SQL optimisation, and data modelling, delivering reliable and cost-efficient solutions for enterprise analytics. He is passionate about continuous learning, mentoring teams, and driving data-driven decision-making.

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