Power BI report authors and BI teams are well-served to remain conscience of both the advantages and limitations of custom visuals. For example, when several measures or dimension columns need to be displayed within the same visual, custom visuals such as the Impact Bubble Chart and the Dot Plot by Maq Software may exclusively address this need. In many other scenarios, a trade-off or compromise must be made between the incremental features provided by a custom visual and the rich controls built into a standard Power BI visual.
In this tutorial, we show how to add a custom visual to Power BI and explore 4 powerful custom visuals, and the distinct scenarios and features they support.
The Power BI tutorial is taken from Mastering Microsoft Power BI. Learn more – read the book here.
Custom visuals available in AppSource and within the integrated custom visuals store for Power BI Desktop are all approved for running in browsers and on mobile devices via the Power BI mobile apps. A subset of these visuals have been certified by Microsoft and support additional Power BI features such as email subscriptions and export to PowerPoint. Additionally, certified custom visuals have met a set of code requirements and have passed strict security tests. The list of certified custom visuals and additional details on the certification process is available here.
Adding a custom visual
Custom visuals can be added to Power BI reports by either downloading .pbiviz files from Microsoft AppSource or via the integrated Office Store of custom visuals in Power BI Desktop. Utilizing AppSource requires the additional step of downloading the file; however, it can be more difficult to find the appropriate visual as the visuals are not categorized. However, AppSource provides a link to download a sample Power BI report (.pbix file) to learn how the visual is used, such as how it uses field inputs and formatting options. Additionally, AppSource includes a short video tutorial on building report visualizations with the custom visual.
The following image reflects Microsoft AppSource filtered by the Power BI visuals Add-ins category:
Selecting Import from store launches an MS Office Store window of Power BI Custom Visuals. Unlike AppSource, the visuals are assigned to categories such as KPIs, Maps, and Advanced Analytics, making it easy to browse and compare related visuals. More importantly, utilizing the integrated Custom Visuals store avoids the need to manage .pbiviz files and allows report authors to remain focused on report development.
As an alternative to the VISUALIZATIONS pane, the From Marketplace and From File icons on the Home tab of the Report view can also be used to add a custom visual. Clicking the From Marketplace icon in the follow image launches the same MS Office Store window of Power BI Custom visuals as selecting Import from store via the VISUALIZATIONS pane:
In the following image, the KPIs category of Custom visuals is selected from within the MS Office store:
Organizations can also upload custom visuals to the Power BI service via the organization visuals page of the Power BI Admin portal. Once uploaded, these visuals are exposed to report authors in the MY ORGANIZATION tab of the custom visuals MARKETPLACE as per the following example:
This feature can help both organizations and report authors simplify their use of custom visuals by defining and exposing a particular set of approved custom visuals. For example, a policy could define that new Power BI reports must only utilize standard and organizational custom visuals. The list of organizational custom visuals could potentially only include a subset of the visuals which have been certified by Microsoft. Alternatively, an approval process could be implemented so that the use case for a custom visual would have to be proven or validated prior to adding this visual to the list of organizational custom visuals.
Power KPI visual
Key Performance Indicators (KPIs) are often prominently featured in Power BI dashboards and in the top left area of Power BI report pages, given their ability to quickly convey important insights. Unlike card and gauge visuals which only display a single metric or a single metric relative to a target respectively, KPI visuals support trend, variance, and conditional formatting logic.
For example, without analyzing any other visuals, a user could be drawn to a red KPI indicator symbol and immediately understand the significance of a variance to a target value as well as the recent performance of the KPI metric. For some users, particularly executives and senior managers, a few KPI visuals may represent their only exposure to an overall Power BI solution, and this experience will largely define their impression of Power BI’s capabilities and the Power BI project.
Given their power and important use cases, report authors should become familiar with both the standard KPI visual and the most robust custom KPI visuals such as the Power KPI Matrix, the Dual KPI, and the Power KPI. Each of these three visuals have been developed by Microsoft and provide additional options for displaying more data and customizing the formatting and layout.
The Power KPI Matrix supports scorecard layouts in which many metrics can be displayed as rows or columns against a set of dimension categories such as Operational and Financial. The Dual KPI, which was featured in the Microsoft Power BI Cookbook (https://www.packtpub.com/big-data-and-business-intelligence/microsoft-power-bi-cookbook), is a good choice for displaying two closely related metrics such as the volume of customer service calls and the average waiting time for customer service calls.
One significant limitation of custom KPI visuals is that data alerts cannot be configured on the dashboard tiles reflecting these visuals in the Power BI service. Data alerts are currently exclusive to the standard card, gauge, and KPI visuals.
In the following Power KPI visual, Internet Net Sales is compared to Plan, and the prior year Internet Net Sales and Year-over-Year Growth percent metrics are included to support the context:
The Power KPI provides many options for report authors to include additional data and to customize the formatting logic and layout. Perhaps its best feature, however, is the Auto Scale property, which is enabled by default under the Layout formatting card.
For example, in the following image, the Power KPI visual has been pinned to a Power BI dashboard and resized to the smallest tile size possible:
As per the preceding dashboard tile, the less critical data elements such as July through August and the year-over- year % metric were removed. This auto scaling preserved space for the KPI symbol, the axis value (2017-Nov), and the actual value ($296K). With Auto Scale, a large Power KPI custom visual can be used to provide granular details in a report and then re-used in a more compact format as a tile in a Power BI dashboard.
Another advantage of the Power KPI is that minimal customization of the data model is required. The following image displays the dimension column and measures of the data model mapped to the field inputs of the aforementioned Power KPI visual:
The Sales and Margin Plan data is available at the monthly grain and thus the Calendar Yr-Mo column is used as the Axis input. In other scenarios, a Date column would be used for the Axis input provided that the actual and target measures both support this grain.
The order of the measures used in the Values field input is interpreted by the visual as the actual value, the target value, and the secondary value.
In this example, Internet Net Sales is the first or top measure in the Values field and thus is used as the actual value (for example, $296K for November). A secondary value as the third measure in the Values input (Internet Net Sales (PY)) is not required if the intent is to only display the actual value versus its target.
The KPI Indicator Value and Second KPI Indicator Value fields are also optional. If left blank, the Power KPI visual will automatically calculate these two values as the percentage difference between the actual value and the target value, and the actual value and the secondary value respectively. In this example, these two calculations are already included as measures in the data model and thus applying the Internet Net Sales Var to Plan % and Internet Net Sales (YOY %) measures to these fields further clarifies how the visual is being used.
Many different KPI Indicator symbols are available including up and down arrows, flags, stars, and exclamation marks. These different symbols can be formatted and then displayed dynamically based on the KPI Indicator Index field expression. In this example, a KPI index measure was created to return the value 1 or 2 based on the positive or negative value of the Internet Net Sales Var to Plan % measure respectively:
Internet Net Sales vs Plan Index = IF([Internet Net Sales Var to Plan %] > 0,1,2)
Given the positive 4.6 percent variance for November of 2017, the value 1 is returned by the index expression and the green caret up symbol for KPI 1 is displayed. With five available KPI Indicators and their associated symbols, it’s possible to embed much more elaborate logic such as five index conditions (for example, poor, below average, average, above average, good) and five corresponding KPI indicators.
The standard slicer visual can display the items of a source column as a list or as a dropdown. Additionally, if presented as a list, the slicer can optionally be displayed horizontally rather than vertically. The custom Chiclet Slicer, developed by Microsoft, allows report authors to take even greater control over the format of slicers to further improve the self-service experience in Power BI reports.
In the following example, a Chiclet Slicer has been formatted to display calendar months horizontally as three columns:
Additionally, a dark green color is defined as the Selected Color property under the Chiclets formatting card to clearly identify the current selections (May and June). The Padding and Outline Style properties, also available under the Chiclets card, are set to 1 and Square respectively, to obtain a simple and compact layout.
Like the slicer controls in Microsoft Excel, Chiclet Slicers also support cross highlighting. To enable cross highlighting, specify a measure which references a fact table as the Values input field to the Chiclet Slicer. For example, with the Internet Net Sales measure set as the Values input of the Chiclet Slicer, a user selection on a bar representing a product in a separate visual would update the Chiclet Slicer to indicate the calendar months without Internet Sales for the given product. The Disabled Color property can be set to control the formatting of these unrelated items.
Chiclet Slicers also support images. In the following example, one row is used to display four countries via their national flags:
For this visual, the Padding and Outline Style properties under the Chiclets formatting card are set to 2 and Cut respectively. Like the Calendar Month slicer, a dark green color is configured as the Selected Color property helping to identify the country or countries selected—Canada, in this example.
The Chiclet Slicer contains three input field wells—Category, Values, and Image. All three input field wells must have a value to display the images. The Category input contains the names of the items to be displayed within the Chiclets. The Image input takes a column with URL links corresponding to images for the given category values. In this example, the Sales Territory Country column is used as the Category input and the Internet Net Sales measure is used as the Values input to support cross highlighting. The Sales Territory URL column, which is set as an Image URL data category, is used as the Image input. For example, the following Sales Territory URL value is associated with the United States: http://www.crwflags.com/fotw/images/u/us.gif.
Impact Bubble Chart
One of the limitations with standard Power BI visuals is the number of distinct measures that can be represented graphically. For example, the standard scatter chart visual is limited to three primary measures (X-AXIS, Y-AXIS, and SIZE), and a fourth measure can be used for color saturation. The Impact Bubble Chart custom visual, released in August of 2017, supports five measures by including a left and right bar input for each bubble.
In the following visual, the left and right bars of the Impact Bubble Chart are used to visually indicate the distribution of AdWorks Net Sales between Online and Reseller Sales channels:
In its current release, the Impact Bubble Chart does not support the formatting of data labels, a legend, or the axis titles. Therefore, a supporting text box can be created to advise the user of the additional measures represented. In the top right corner of this visual, a text box is set against the background to associate measures to the two bars and the size of the bubbles.
Dot Plot by Maq Software
Just as the Impact Bubble Chart supports additional measures, the Dot Plot by Maq Software allows for the visualization of up to four distinct dimension columns. With three Axis fields and a Legend field, a measure can be plotted to a more granular level than any other standard or custom visual currently available to Power BI. Additionally, a rich set of formatting controls are available to customize the Dot Plot’s appearance, such as orientation (horizontal or vertical), and whether the Axis categories should be split or stacked.
In the following visual, each bubble represents the internet sales for a specific grouping of the following dimension columns: Sales Territory Country, Product Subcategory, Promotion Type, and Customer History Segment:
For example, one bubble represents the Internet Sales for the Road Bikes Product Subcategory within the United States Sales Territory Country, which is associated with the volume discount promotion type and the first year Customer History Segment. In this visual, the Customer History Segment column is used as the legend and thus the color of each bubble is automatically formatted to one of the three customer history segments.
Despite its power in visualizing many dimension columns and its extensive formatting features, data labels are currently not supported. Therefore, when the maximum of four dimension columns are used, such as in the previous example, it’s necessary to hover over the individual bubbles to determine which specific grouping the bubble represents, such as in the following example:
If you found this tutorial useful, do check out the book Mastering Microsoft Power BI and develop visually rich, immersive, and interactive Power BI reports and dashboards.