Building upon the extensive selection of visualizations discussed in previous Power BI blog, we explored various powerful visualizations, including Bar and Column, Line and Area, Waterfall, Funnel, and Scatter plots in the first part. In this second installment of the blog series, I will present an overview of additional chart types, such as Pie, Donut, and Treemap charts, Maps, Gauges, Cards, and KPIs.

Getting right into it we’re going to jump straight into this section on ‘Pie’, ‘Donut’ and ‘Treemap’ charts. In this group I have the Pie Chart (highlighted in red in Figure 1), the Donut Chart (highlighted in blue in Figure 1), and the Treemap (highlighted in green in Figure 1).

The first thing on the docket for this section is the ‘Pie’ chart. ‘Pie’ charts are popular visualizations that are used to show different datapoints as part of a whole. In this case the ‘whole’ is the ‘Sum of the Sales’ and each part of the whole is the ‘Country’ where sales are taking place.

Next up we have the ‘Donut’ chart. ‘Donut’ charts are exactly like ‘Pie’ charts, except they’re shaped like a donut. Just like a ‘Pie’ chart, ‘Donut’ charts are used to show different datapoints as part of a whole. In my ‘Donut’ chart, the ‘Sum of all the Profit’ is the ‘whole’ and each part of the whole are the ‘Product(s)’ being sold. Note that in cases like my ‘Pie’ chart, these are probably not the best visual to use as it can be easy to misinterpret the data.

Moving forward to the last topic of this section, we have the ‘Treemap’. ‘Treemap’ can be very useful if used correctly. Take note of the overall structure, which forms a sizable rectangular shape. Inside this large rectangle, you’ll find colored rectangles, each containing smaller nested rectangles (I understand that was quite a description). ‘Treemap’ work by forming a hierarchy of nested rectangles which all act as parts of a whole, similar to the ‘Pie’ chart and ‘Donut’ chart Within my ‘Treemap’ visualization titled Sum of Units Sold by Month Name and Product,’ each of the rectangles serves as a representation of the total ‘Sum of Units Sold.’. Moving down in the hierarchy, we see 12 different boxes all with a different size, different color, and a different month name. This is to show the ‘Sum of Units Sold’ in each ‘Month’, the larger the box, the larger the ‘Sum of Units Sold’ for that ‘Month’. Moving to the last level of our hierarchy, we see all of the different ‘Product’ names within each ‘Month’. This is to represent the ‘Sum of Units Sold’ from each ‘Product’ in that ‘Month’. Analyzed.

Speaking of maps, our next section is dedicated to various ‘Map’ options. In this group I have the Map (highlighted in red in Figure 2), the Filled Map (highlighted in blue in Figure 2), and the Shape Map (highlighted in green in Figure 2). Now I will not be displaying the other two map types as they require other applications or special permissions, but I will still provide an overview of them.

Let’s start with the fundamental ‘Map’ visualization. In my ‘Map’ visualization, titled ‘Sum of Units Sold by Country and Country,’ it’s worth noting that the term ‘Country’ is duplicated. The reason for this duplication is that I’ve utilized ‘Country’ both as the ‘Location’, where the map positions the data points, and as part of the ‘Legend’ to assign distinct colors to each country. A ‘Map’ is used to show a geographical representation of different categories of data points. For example, in my ‘Map’ visual, the different bubbles are meant to show the ‘Sum of Units Sold’ and their location represents which ‘Country’ the units are being sold in.

Second on the agenda for this section is the ‘Filled Map’. The ‘Filled Map’ is used to illustrate the values of different locations through the use of diverse colors. Similar to the previous map, the map that I used in ‘Sum of Profit by Country and Country’ uses ‘Country’ as both the ‘Location’ and the ‘Legend’ values.

Last up in the ‘Map’ section is the ‘Shape Map.’ The primary objective of the ‘Shape Map’ is to distinguish regions on a map by applying varying colors to them for comparison. It doesn’t show precise geographical locations of data points. A benefit of this ‘Map’ is its heightened level of customization since it utilizes .Json files to present the specific map you desire.

Now, turning our attention to the maps for which I don’t have visual representations, we have the ‘Azure Map’ and the ‘ArcGIS Map’ for Power BI. The ‘Azure Map’ is used to show location-based context on how data interacts with and influences the user’s business. ‘Azure Map’ has much stronger geospatial analysis capabilities compared to the standard ‘Map’ visual. ‘ArcGIS Map’ is another powerful map visual that has more accurate geographical data. It can use geography, location, and even different demographics in order to deliver the data you are looking for more effectively.

The last section I will be covering is the ‘Gauge’, ‘Card’, and ‘KPI’ chart. In this group I have the Gauge Chart (highlighted in red in Figure 3), the Card (highlighted in blue in Figure 3), the Multi-Row Card (highlighted in green in Figure 3), the KPI Chart (highlighted in purple in Figure 3), and the New Card (highlighted in Orange in Figure 3).

In this section, the visuals are meant to highlight specific metrics. First up is the ‘Gauge’ visual. The ‘Gauge’ is used to show progress towards a particular goal. It displays the minimum value, the maximum value, and the current value against the target which in this case is the maximum value.

Next are the ‘Card’ visuals. The ‘Card’ visual is designed to call attention to a specific metric. It is only able to hold one data point and can also utilize conditional formatting to change the color of the value contained in the card in order to show whether or not it has met the target value. The ‘Multi-Row Card’ is meant to display numerous data points in order to showcase performance of specific metrics or compare them in rows and/or columns. Last up in the ‘Card’ visuals is the ‘New Card’ visual. The ‘New Card’ combines the best of both worlds from the ‘Card’ and the ‘Multi-Row Card.’ The ‘New Card’ has the same large callout values that the original ‘Card’ has but also can display multiple different values side by side.

For the last visual we will cover in this section and blog is the ‘KPI’ (Key Performance Indicator). The ‘KPI’ visual is a very powerful asset that is used to display how specific metrics are performing. If your values surpass the target, the visualization will showcase a green background on the chart. It will present a bold green callout value with a checkmark and display the goal, along with the percentage by which the value exceeds that goal below. If the entered value falls below the target, the visualization will depict a red background on the chart. It will present a bold red callout value with an exclamation point next to it and display the goal, along with the percentage by which the entered value is below the target, below.

I realize that was a substantial amount of information, so I’ll wrap up the blog here. I hope you have a wonderful day! If you haven’t read Part 1 you can click here and for Part 3 you can click here. If you would like to stay updated on when we post blogs you can subscribe by leaving a comment and checking the subscribe box or by filling out information on the main/archive blog page.

Bailey McDonald
Data Engineer, Patriot Consulting
Email: | Blogs: Patriot Consulting Blogs
LinkedIn: Personal: BaileyMcDonald | Company: Patriot Consulting

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