30 Days to Success in Power BI: Day Four Our First Visualization
Welcome back to day four of our series on Success in Power BI! With 30 days of Power BI learning, we should be able to be successful with our use of the desktop tool. Have you forgotten where we left off from day three? If so, here is the link to refresh your memory.
So let’s create a visualization today in Power BI. For clarity’s sake, the Power BI desktop consists of reports, visualizations, and datasets. We’ve already built a dataset in the previous couple of days. Now, there is a difference between reports and visualizations. A visualization might be a pie chart or a map. A report, however, can contain one or many visualizations in order to present your data insight. Therefore it might contain a pie chart and a map to present the data cohesively in order to understand the insight we are presenting. Make sense?
So let’s get started. If you look at Figure 1, you’ll see the red arrow pointing to the available visualizations. You’ll also see where I clicked on the ellipses icon in the bottom right area and brought up a menu to import visuals (another name for visualizations). I am mentioning this to let you know that you can download custom visualizations!! Some are pretty fun and create memorable visuals for your intended audience. You can download these at https://app.powerbi.com/visuals/ and install them on your Power BI Desktop installation. For our purposes, however, we will stick with the standard visuals for now until we get up and running.
The first step to creating a visualization on our blank canvas is to choose one from the Visualizations area (highlighted in Figure 1) and click on it. We are going to select the Line Chart visual which is highlight in Figure 2 (first on the left of the second row from the top). This will drop a blank line chart visual onto your page as shown in Figure 2 on our white page.
Now you can see the dark area (called Fields and Filter pane) below the visualizations has changed between Figure 1 and Figure 2, depending upon the visual that was selected. This is probably the most difficult part of Power BI, in my opinion, as these titles do not seem very intuitive to the lay person (nor me the data professional, lol).
For this line chart, we want to see Hank Aaron’s batting average by his Age as players’ performance tends to decline as they age (as do all of us eventually). So if you look to the far right, you can see our data set fields. From here we can drag the batting average (depicted as BA) field over to the Values slot and then the Age field to the Axis slot. We will now see hit batting average on the Y axis and the age across the X axis as shown in Figure 3.
Obviously, we cannot see this visual so let’s grab the bottom corner and drag it across the page as shown in Figure 4. Not sure if you have the data in the right slots? Try different configurations to see if this is the insight you are trying to communicate. I tried reversing these and it made no sense in this situation. We really want to see an increase or decrease as the player ages.
So now if you look at Figure 5, this is what we saw on the original web page for Hank Aaron’s major league batting statistics from Baseball-Reference.com. We have now taken our batting dataset and turned it into a workable visual. It’s not pretty. Yet. This is a great stopping point. See you on day five!