14. The Analytics Pane

Overview

The Analytics pane allows you to add various reference lines to charts, such as average, min, max and constant lines. We’ll create some of these lines in this lesson.

To explore more Kubicle data literacy subjects, please refer to our full library.

Summary

  1. Lesson Goal (00:10)

    The goal of this lesson is to use the analytics pane to add reference lines to charts.

  2. Using the Analytics Pane (00:25)

    To access the Analytics pane, we select a chart, then select the Analytics icon below the visualizations pane. This icon has the appearance of a magnifying glass. 

    When we open the pane, we see a list of the reference lines we can add to the chart. The exact lines available vary based on the chart type, but typically includes constant lines, average lines, min and max lines, and other reference lines. Note that some chart types don’t support any reference lines.

  3. Adding a Constant Line (01:00)

    A constant line is a straight line with a single value. Here we use it to compare monthly user numbers against a company target. To add a constant line, we select constant line from the analytics pane, then add. We then need to enter the constant value for the line, and it will be added to the chart.

    After creating the line, there are many options for formatting it. For example, we can name the line, adjust its color, adjust the line style, and so on.

  4. Adding an Average Line (01:50)

    An average line adds a constant line to a chart, based on the average value of the data in the chart. To add an average line, we select average line from the analytics pane, and add. As before, we can format the line, extensively. We can also include a data label which indicates the value of the average line.

    If the data in the chart updates, then the average line will be recalculated automatically. For example, we remove two sales people from our data set, as they appear to be outliers. Our average line correctly recalculates the average users per sales person when we do this.

Transcript

In the previous lesson, we learned how charts can be used to filter each other through interactions.

In this lesson, we'll look at how we can use the Analytics pane to add dynamic reference lines to our charts. These can be particularly useful when evaluating performance as they can allow us to compare data with targets, averages, or other useful metrics.

We'll examine the analytics pane using the visuals we created in the previous lesson.

To bring up the analytics pane, we'll need to select one of our visuals.

We'll select the line chart and then select the analytics icon below the visualizations pane. We now have the ability to add a constant line, a min or max line, an average or median line or a percentile line.

The exact selection of lines various according to the type of chart. Note that some chart types do not support analytics features. Our software company has a target of selling to 42,000 users a month. A constant line can help us easily see if we're reaching this target. We'll select constant line, then add and enter 42,000 as the value.

We'll now format the line, we'll double-click Constant line 1 and change the name to Target Users.

We'll then change the style to dotted and then a data label would display units as thousands.

Next, we'll make the line easier to see by reducing the transparency to zero.

It's now apparent when monthly sales are above or below our target number of users. Let's move on to the bar chart of users by salesperson.

Suppose we want to know the average number of users that each sales person has brought in. As we head back to the analytics pane, we see the same formatting options.

We'll add an average line and name it, average users.

This time we'll make the line stand out by changing the color to yellow.

Again, we'll reduce the transparency to zero and add a data label.

In order to see the label, we'll change the vertical position setting to under, to put it at the bottom of the chart.

We can see that the average salesperson has brought in just under 33,000 users.

Note that these analytics lines are dynamic.

Imagine we want to leave out the bottom to salespeople as they're clearly outliers. To do this, we'll expand the filter pane and we'll modify the visual level filter for salesperson.

We'll select all and then de-select both Barcus and Scefani.

Now that they're gone, you can see at the average line has moved up to 37,223. This dynamic aspect of the analytics lines can be very useful when you're frequently interacting with your graphs. Let's stop the lesson here. The analytics offered may not be particularly advanced, but their dynamic nature makes them handy tools for your visualizations. In the next lesson, we'll look how to create bubble and scatter plots.

Dashboards and Visualizations
Introduction to Visualizations in Power BI