This style of chart is normally limited to multivariable types of data, with only two or three data points involved.  Because of the type of data best revealed in this type of chart it’s not good practice to plot multiple data points in a radar chart - too much data will make the chart messy and confusing to read.  Using our example data there are six data points, so it all starts to blend.  Can you decipher all six data points?  I can’t!  So, in this case, a radar chart isn’t our best choice.

Line charts are best used to show how values develop over time, or how different categories rank against each other.  In our case, we need each application as a standalone entry, to show their expenses over each month of CY2018. However, the line chart displays the values so closely together that they overlap.  Is this easily revealing the data we need to see in our chart?  With some work, possibly!  However, let’s see if our last chart type, the column chart, will do a better job.

Column Chart:

Column charts are useful for showing data changes over a time period while illustrating a comparison across items in the chart.  This is the same as the bar chart we mentioned originally. Both types could work for our needs but look at the grouping of the data.  The column chart shows our grouped month by month data most clearly out of the charts we’ve tried, with the side-by-side comparison of different application cost values per month.  We haven’t taken any extra configuration steps and this chart already shows our information in the clearest way possible.  Great!  We’re on our way towards telling a clearer story with our data. 


Apptio Reporting Surface – Chart Color Customization

Now we need to remember what the focus of this chart is.  We’ve taken the first step, recognizing our most expensive items by month.  Now about the second part of the request: how do we highlight which of these applications are the most expensive?  The answer is colors!  Colors in a chart can draw eyes to a specific data point, or entire set of data points, to highlight the story we’d like to tell.  

Let’s think about the current colors in our chart.  Do the default colors help us tell that story?  Are we highlighting our most expensive applications clearly?  With the similar shadings of blues and grays in our chart, it really doesn’t seem so!  None of these colors stand out significantly from the other columns except by height.  So how can we change the colors of our chart to highlight needed data points more clearly?

Multi-Color Highlighting:

Multi-color highlighting is one color option we can apply, where multiple data points can be given a unique and distinct color compared to others.  Wh this chart now? Where are your eyes being drawn?  I’ve specifically highlighted the three most expensive applications for review using brighter colors that your eyes are naturally drawn to. This makes it easy to see how these three applications are our largest cost drivers, especially by highlighting our largest cost driver with its own standout color.  Our audience no longer searches for data - we’re clearly showing it.

Single Color Highlighting:

Single color highlighting is another color option we can apply, where only one data point is given a unique color.  What story are we telling now?  We're clearly singling out the Amazon Web Services application as our major cost driver.  I want my audience to pay special attention to this specific application, so I’ve added it in orange, while leaving the rest of my chart in muted blues and grays.  I’m not directing attention to our two second-most expensive applications now, though I may do that later.  For my specific needs, I need to highlight that we have a high amount of AWS Services, we need to concentrate on our spend there first.

Remember that in reporting the visualizations can tell just as much a story as any written word.  Concentrate on telling your visual story as clearly as possible.  Think of these questions as you build your own visualizations:

• Can I easily tell what the most important data points are?
• Can I easily tell the difference between the different data points?
• Can I easily tell what this chart is trying to tell me?

There are many more techniques to use, I definitely haven't touched on all of them.  I encourage all of you to share your own best practices, your own methods of drawing attention to your own data.  I'll be looking forward to hearing your feedback as well!