The Dashboard Builder has more than 50 built in charts and widget items for you to use. You can easily pick the items and insert them into your dashboards.
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In this article, we will focus on the following widget items:
When you go to your dashboard and enter edit mode, click on the + Add item button and you will see the following:
1. Text
After you add a Text item to the dashboard, you can click on it and edit the content.
2. Image
Add an image item to your dashboard, hover over it, and click the settings button. You can input an image URL or upload an image directly from your local device. Pick the mode to adjust the alignment of your image file.
You can put a logo or any other images on your dashboard to customize the look.
3. Number with evolution
This widget is ideal for showing metrics that evolve over time. In the context of an assessment, you likely have custom scores based on respondents’ answers.
Example:
For a risk assessment, there’s a custom score that determines the overall “risk level” for each respondent. As a consultant or HQ manager, you can view the average risk level over time based on all submitted responses to identify trends.
Start by adding the item to your dashboard. Hover over the widget and click on Data.
You need to drop two data points onto the widget:
- Measure: The metric (KPI) you want to display, such as the risk level determined by the custom score.
- Evolution: The time frame for comparison, such as vs. last month, vs. last week, vs. last hour, etc.
In this example, I select Responses dataset -> custom score. Click on custom score, drag it and drop it on the Measure label.
By default, the sum of the values in that specific column will be displayed. You can easily change the aggregation to e.g. average via the slot menu settings. Here, you can also adapt the number format.
Click on the settings icon next to the label Measure: custom_score. Click on the Aggregation dropdown and change it to Average.
Then you will see the following, you can change the title from custom_score to, for example, Risk level.
Now we need to find the timeframe and drop it to the widget on the evolution label.
Go back to Responses dataset and scroll down, you will find server_date_completed. This shows the time when the responses are submitted. In my case, I want to see the evolution of risk levels vs. last week. So I select Week and drop it onto the Evolution label on the widget.
There you go.
4. Video
Add a video widget to the dashboard. Click on the settings icon next to your video widget. On the right hand side. You can insert web links or just select the option to input a youtube link.
There are other settings options below:
- Show controls: The viewer can play and pause the video.
- Auto play: The video starts playing automatically.
- Loop video: The video plays in a loop.
5. Table
Table is the right choice if you want an unaggregated, detailed view of your data. In the Dashboard Builder, the tables serve this purpose
Tables in the Dashboard Builder are designed to present raw, row-level data. Unlike other charts, it doesn't do any fancy aggregations, keeping it unique and straightforward.
You can use the tables for:
- Matrix display: For data that naturally fits into a matrix or tabular format with specific rows and columns.
- Data review and comparison: Use it when you want to dive deep into your data, examining exact values, not just visuals. Rearranging your data fields is simple. Navigate to the 'Columns' section and adjust them to your desired sequence.
Select the table widget and add it to your dashboard.
Now your can drag and drop data points to the table. Each data represents a column. In the example below, I want to show each of the responses with their location, questionnaire completion time, and the result of the risk level based on the formula.
Click on the table icon (data) next to the widget. Click the settings icon in the middle.
Here you can easily rearrange the order of the columns and change the column headers.
Sorting in the table
In the settings section of the table (Settings>Interactivity>Sorting), you can choose how the sorting of the table is going to work:
Two options are available:
- Multi-column sorting: This is the default option when you create a table. It provides the ability to sort more than one column and create an advanced sorting to fit more complex requirements. The first column sorted is the primary sorting column. Then additional sorting can be added by clicking on other columns
- Single-column sorting: This option allows the sorting on only one column. Clicking on a column will set the table sorting and when clicking on another column the table sorting will change based on the column clicked.
6. Pivot table
Use pivot tables in case you want to summarize your data, group them together and apply certain calculations. It allows you to transform columns into rows and the other way around.
6.1 Create a pivot table
Select the pivot table widget and add it to your dashboard. By clicking on the ‘data’ settings, you can see the three different data labels you can add data to : columns, rows and measures.
6.2 Columns
Common data points to use:
- Dates (Response submissions): To see number of responses aggregated by certain timeframes.
For each value in your added column, a column appears in the pivot table. You can add multiple columns to this slot, which will be displayed as a waterfall. The column added first will function as the highest level. You can easily switch the levels in the data settings of the chart, as you can see in the illustration below.
The numbers displayed in the white area are the number of rows for each value in your dataset, since we have not yet added a measure. In the example below we see the number of rows per month.
6.3 Rows
Common data points to use:
- Categories, teams, locations to aggregate data
Drop the data to the row labels so your data will be aggregated with corresponding rows and columns.
In the following example, I want to see number of responses per region (intro field) every hour. You can freely drag and drop the data you want to compare. In this below, you see there are already numbers in the cells in between. Because it automatically calculates the number of responses matching the rows and columns.
6.4 Measures
Data points that have numerical values are great for this label.
By adding data to the measure label, you create enhanced and multidimensional insights in your data.
When adding more than one column to the measure label, extra columns will be created on top which might become complicated. Make sure your pivot table stays easy to read.
By default, the sum aggregation is enabled. You can change this to e.g. average in the settings of the measure label.
In the previous step (the screenshot above), the tables shows the number of responses per hour per region. Now let's take it one step further.
I want to see the risk levels (it's a formula results) per hour per region. I select the dataset Formula -> and the data result, and drop it on the Measure label.
And now I can see the risk levels:
You might notice the data looks strange. Some numbers are above 100. Because by default, it shows the "sum" aggregation. You can change the aggregation by doing the following steps:
Click on the data icon next to your pivot table:
Click the settings icon in the middle of the pivot table, on the Measure label.
In this example, I want to see the average. Therefore, I can change the aggregation to Average. And also change the Decimals from 2 to 0 digits.
Now I can see the average risk level in different time frame across different regions!
6.5 Sorting
After adding your data, you can change the way of sorting by clicking on the titles of the columns and rows. The little arrows indicate whether the values are sorted ascending or descending.
In the settings of the chart, you can always reset all the sortings you implemented.
Understanding how sorting on a pivot table works is essential for effectively organizing and analyzing data within your pivot tables.
The sorting in pivot tables ensures that previously sorted columns or rows retain their order when applying subsequent sorting to the measures criteria. To better illustrate this concept, let's consider an example using the customer names and associated product amounts in the above chart.
7. Spacer
You can also add a spacer in between other widgets on your dashboard to customize the look.
What's next?
- Dashboard Builder: datasets explained: Check detailed explanations on the datasets available for your to connect to your
- Getting started with the filter widgets on your dashboard: Widget items: filters
- Check out these widgets to turn your dashboard data into meaningful insights:
Don't want to build it yourself? Contact our professional services team
