Bullet Chart Sparklines in Power BI

If the goal is an actual comparison, it’s hard to beat the bullet chart. Highly efficient in terms of the amount of space they take up, with excellent data to ink ratio, they are both immediately intuitive yet data-dense without relying on loud distracting colors. The downside is that up until a week ago you could have them as a sparkline in a table which is where you need them the most.

In this video, we’ll take you through building a bullet chart measure from nothing but an SVG snippet of code. This may well become your favorite new visual, and you’ll be able to use the techniques in these videos to start thinking about how to create your own SVG sparklines and small multiples.

The Code

My Favorite Bullet Chart = 
VAR vBaseText = 
"data:image/svg+xml;utf8, _svg width=""100"" height=""100"" version=""1.1"" xmlns=""http://www.w3.org/2000/svg"" style=""background: %23ffffff""_
  _rect  x=""0""     y=""25""   rx=""2"" ry=""2""   width=""100""     height=""50""   style=""fill:%23f2f2f2;stroke-width:0;fill-opacity:1"" /_ 
  _rect  x=""0""     y=""45""   rx=""2"" ry=""2""   width=""#Actual"" height=""10""   style=""fill:%23333333;stroke-width:0;fill-opacity:1"" /_
  _rect  x=""#Goal"" y=""30""   rx=""2"" ry=""2""   width=""6""       height=""40""   style=""fill:%23888888;stroke:black;stroke-width:0;fill-opacity:1;stroke-opacity:1"" /_

VAR vObjects = ALL( Sales[Location], Sales[City],Sales[Country],Sales[State/Province] )

VAR vMaxActual = MAXX( vObjects, [Total Sales] )
VAR vMaxGoal   = MAXX( vObjects, [Total Goal]  )

VAR vXAxisRangeBase = MAX( vMaxActual, vMaxGoal )

VAR vActual = INT( DIVIDE( [Total Sales], vXAxisRangeBase ) * 90 )
VAR vGoal   = INT( DIVIDE( [Total Goal],  vXAxisRangeBase ) * 90 )

VAR vReturn = SUBSTITUTE( SUBSTITUTE( vBaseText, "#Actual", vActual ), "#Goal", vGoal )

RETURN IF( [Total Sales], vReturn, BLANK() )
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Brian Grant
Brian Grant

Brian Grant is a masterful Senior Analytics Consultant by day, and a Power BI legend by night. A passion for Power BI drove him to holistically master the tool from all three perspectives: M, DAX, and the visualization layer. Brian is a constant teacher who leads Power BI training sessions, while sharing his wealth of expertise through video and blogging resources.

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