Counting multiple duplicate columns by a distinct column.

jarivera777 , You can use UNPIVOT for this

Unpivot the Impact Columns:

Go to the "Transform Data" option to open Power Query Editor.
Select the columns Impact 1 to Impact 5.
Right-click and choose "Unpivot Columns". This will transform your data from a wide format to a long format, creating two new columns: Attribute (which will contain the original column names) and Value (which will contain the Impact colors).

Filter the Value column to remove any blank entries.
Create a Distinct Column:

In Power Query Editor, select the Value column.
Go to the "Remove Duplicates" option to create a distinct list of Impact colors.
Count Instances of Each Color:

Close and apply the changes to load the data back into Power BI.
Create a new measure to count the instances of each color:

DAX
ColorCount = COUNTROWS('YourTable')

Create the Visual:
Use a bar chart or any other suitable visual.
Set the Value column as the axis and the ColorCount measure as the value.

To expand upon bhanu_gautam 's answer, you can do the whole transformation in Power Query. 
Here is an example code you can paste into the advanced editor of a blank query so you can review each step needed. 
The end result will look something like this...

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("bZG9DoMwDITfJTMojfkLa/eqpVuFGKI2YmgEFSri9ZsY4qCGBc6E+2xf2pYJljDgksMJcisbkW7qrl/0vE5q6LUVZzPjaxqXgXVJy8BWBS/JDt6+/UnOFfTQxoyLFWjOrBC8invf5uljon6uVM93wDhGjgPIeICL6vXwVfum4ZMHIqKwQq4IN1GTpZsio+9L24QTSqK0Vc2hiDF/GYQp6AABFW4iBAEgioPEwXLIkC5RWO8DGXm0y/5eD9aoHUHwOib4zGjqOA3WdT8=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [ID = _t, #"Closed Date" = _t, #"Qtr/Yr" = _t, #"Impact 1" = _t, #"Impact 2" = _t, #"Impact 3" = _t, #"Impact 4" = _t, #"Impact 5" = _t]),
    #"Changed Type" = 
    Table.TransformColumnTypes(
        Source,
        {
            {"ID", Int64.Type}, {"Closed Date", type date}, {"Qtr/Yr", type text}, {"Impact 1", type text}, {"Impact 2", type text}, {"Impact 3", type text}, {"Impact 4", type text}, {"Impact 5", type text}
        }
    ),
    distinctQuarters = 
    List.Distinct(#"Changed Type"[#"Qtr/Yr"]),
    #"Removed Columns" = 
    Table.RemoveColumns(
        #"Changed Type",
        {"ID", "Closed Date"}
    ),
    #"Unpivoted Other Columns" = 
    Table.UnpivotOtherColumns(
        #"Removed Columns", 
        {"Qtr/Yr"}, 
        "Attribute", 
        "Value"
    ),
    #"Grouped Rows" = 
    Table.Group(
        #"Unpivoted Other Columns", 
        {"Value"}, 
        {
            {"Total", each Table.RowCount(_), Int64.Type}, {"nestedTable", each Table.SelectColumns(_, "Qtr/Yr"), type table [#"Qtr/Yr"=nullable text, Value=text]}
        }
    ),
    groupNested = 
    Table.TransformColumns(
        #"Grouped Rows", 
        {
            {"nestedTable", each Table.Group(_, {"Qtr/Yr"}, {{"qtrCount", each Table.RowCount(_), Int64.Type}})}
        }
    ),
    pivotNested = 
    Table.TransformColumns(
        groupNested, 
        {
            {"nestedTable", each Table.Pivot(_, List.Distinct(_[#"Qtr/Yr"]), "Qtr/Yr", "qtrCount")}
        }
    ),
    expandNested = 
    Table.ExpandTableColumn(
        pivotNested, 
        "nestedTable", 
        distinctQuarters
    ),
    removeBlankColors = 
    Table.SelectRows(
        expandNested, 
        each ([Value] <> "")
    ),
    changeQtrTypes = 
    Table.TransformColumnTypes(
        removeBlankColors,
        {
            {"Q1-2024", Int64.Type}, {"Q2-2024", Int64.Type}, {"Q3-2023", Int64.Type}, {"Q4-2023", Int64.Type}
        }
    )
in
    changeQtrTypes