Create a Custom Dashboard
Purpose: To show you how you can create a new custom dashboard, converting predefined topics (datasets) to customizable data visualizations that your users can analyze and share key insights into your HR data.
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Overview
Adding data visualizations to custom dashboards allows for a more dynamic and interactive presentation of data, as they display multiple analyses. Within a published dashboard, users can apply interactive filters and view comprehensive data at a glance.
The following are key terms to understand as you build your data visualizations and convert them into a dynamic dashboard with interactive insights.
Workbook: A workbook is shown as a tab (+Query) at the bottom of the Manage Dashboards page. Each workbook is an interactive environment designed for creating and editing a data visualization.
Topic: Topics are datasets created by BambooHR that serve as the foundation for building data visualizations.
Fields: There are two field types: dimensions and measures.
- Dimensions are fields that categorize data, typically used on the x-axis. They represent different combinations of values for analysis.
- Measures are quantitative fields that are aggregated using functions like sum, count, or average, typically used on the y-axis to provide numerical insights.
Filters: Filters narrow down data in a workbook. Additional filter options vary based on the field type (number, text, date, etc.).
Formulas: Formulas (or calculations) can be added to a workbook using Excel syntax. Most Excel functions are supported.
Step 1: Choose a dataset
You will first need to select a set of data you want to build data visualizations upon. Navigate to the Reports tab and select Dashboards from the sidebar menu. On the Dashboards page, select Manage Dashboards and then click +New Analysis in the top right corner.
Select a topic from the list.
Within a dashboard, you can add a new data visualization based on any of the default topics.
Step 2: Create data visualizations
After selecting a dataset, you can start adding specific fields from the left column by clicking on the field name. Using the search bar will help you save time looking for a specific field.
- Auto-populated data based on your selections will automatically appear on the Results tab. You can either view the data as results or a chart, or both. The chart option provides data visualization types (bar chart, pie chart, etc.) for you to determine which type best reflects the data you want to analyze.
- The bottom toolbar is where you can add more data visualizations (click the + icon) and rename an existing one (right-click on name > select Rename).
- To rename a data visualization, simply click Query and enter the new name.
Step 3: Add data visualizations to a custom dashboard
Once your data visualizations are all set, you can publish them by clicking +Dashboard in the top right corner and then entering a name for the custom dashboard. Organizing each set of workbooks into a cohesive and unified dashboard helps facilitate easier data interpretation and decision-making.
Step 4: Customize data insights
The following actions (adding filters, controls, etc.) are accessible in the edit version of a custom dashboard that is published.
Add filters
Dashboards have filter capabilities, allowing you to refine and customize data visualizations by selecting a specific criteria. Once you save a filter to an existing dashboard, users with the correct permissions will be able to access the filter(s) when viewing the published dashboard.
To enter the edit version of a dashboard, find your new custom dashboard by clicking Reports > Dashboards > Manage Dashboards. Within the selected dashboard, select Edit in the top right corner.
Next, click Add filter to get started.
Clicking Add filter will bring up a list of fields populated from a dataset (e.g., employee compensation). From the left sidebar menu, determine which fields you want to apply as filters to the workbooks. By default, the filter will be applied automatically to all visualizations that pertain to the selected dataset, but you can choose to remove the filter from certain visualizations.
Data visualizations with a filter will be highlighted in blue. To add or remove a filter, simply click on the blue icon in the top right corner of the visualization.
Each filter added will have additional settings you can configure:
- Label: Name the filter how you want it to appear in the dashboard.
- Description: A description will appear as an informational tooltip when you hover your cursor over the filter. This is optional.
- Filter control: There are two filter control types—advanced and single value dropdown. Advanced allows users to select multiple options while single value only allows the user to select one option.
- *Default value: This option allows you to select a default filter, along with preset conditions, that will be automatically applied to all relevant visualizations within the published dashboard. In the example above, I selected the employment type of "Full-Time," which means the published dashboard will only show data that pertains to full-time employees. *You can leave this setting as "is any value" if you prefer users to apply any filters.
- **Hide this filter: Use this option if you do not want users to access the filter from the published dashboard. The value will still be applied in the background but remains hidden from the user.
- Delete filter: Use this option if you would like to delete the filter.
*Setting the default value to "matches user attribute" will automatically personalize dashboard views. For example, a sales dashboard can dynamically filter data to show each account executive only their own deals.
**Hiding dashboard filters will not restrict access to sensitive data. Instead, we recommend using access level settings to determine who should and should not have access to data in your company's dashboards.
Add controls
The controls feature enable users to switch fields within a data visualization. To add a control, click Add control and select which visualizations it should apply to by toggling the option in the top right corner of the visualization. The following are four main types of controls:
- Field switcher: Enables swapping between one dimensions or measure, like changing from country to city.
- Multi-field switcher: Enables swapping between multiple dimensions or measures, like changing between employee compensation metrics such as base salary and total benefits, or switching between different stages of the hiring process, such as candidates interviewed and candidates hired.
- Time frame switcher: Allow users to easily switch the time frame of the underlying data, such as moving from daily to weekly views.
- Period over period: Facilitates the comparison of two time periods, letting users select and compare different time dimensions directly from the dashboard.
At least one of the fields being controlled must be present in the data visualization for the control to have an effect.
Example
In the example above, the field switcher is used to adjust data visualizations.
Add text tile
Using the Add text tile option, you can use markdown to add text, images, links, and more.
Auto-refresh data
Data in a dashboard can be automatically refreshed for real-time updates. The auto-refresh and facet filter options are turned off by default. Collapsible filters are enabled by default, but you can toggle off that setting if needed.
To enable auto-refresh, click the Edit dropdown menu > Dashboard settings > toggle on Auto-refresh. Then, determine the auto-refresh timeframe and click Update settings to finalize changes.
Facet filters: If enabled, one filter will refine the results of another filter across workbooks within a dashboard. For example, selecting a division filter will narrow down the department options to only departments within the selected division.