|Available for||User roles||Super Admin|
|Packages||LeverTRM for Enterprise and/or Advanced Analytics|
||The Data Explorer will be part of our Spring 2022 product release, scheduled for progressive rollout starting mid-May 2022. For more information on the Spring 2022 release, keep an eye on our Product Release Notes.|
While the dashboards available in Visual Insights provide visibility into key dimensions of your recruitment data, every talent acquisition's reporting needs are different. The Data Explorer allows you to build custom charts from various data sets that you can then add to dashboards, to give you and your team a complete picture of the metrics that matter most. Readers of this article will learn about:
This article covers the steps for building a custom chart using the Data Explorer. For details on the data available to build custom charts, refer to out Data Explorer data sets directory.
Accessing the Data Explorer
||Access to the Data Explorer requires LeverTRM for Enterprise package and/or the Advanced Analytics add-on.|
To access the Data Explorer...
- Navigate to Reports and click the Preview Visual Insights button.
- Click the Data Explorer icon in the left-side navigation.
- Select a data set from which to generate your custom chart.
- For a full list of available data sets and the data fields in each, refer to our Data Explorer data sets directory.
Data Explorer layout
The chart builder in the Data Explorer consists of four sections.
From the picker, you can select the data fields that you will use to build your chart. You can expand and collapse data field groupings in the menu or search for a data field by keyword. As you select data fields in the picker, they will be listed under the 'In Use' header, so you can easily keep track of the fields you have pulled into your report.
Any data fields used as a filter will appear in this section of the chart builder. Here you can define the operators, attributes, and logic for the filter(s). To learn more, refer to our dashboard filters help article.
In this section, you are required to a choose chart type to visualize the data you have selected in the picker. For tips on choosing the best chart option, check out this video on visualization best practices.
This section shows all of the fields you have selected from the picker to make up the data set of the chart you are building. The columns in this table can be reordered and pivoted to suit the nature of the insights you are measuring.
Quick Start options
Upon opening the Data Explorer, you will be presented with Quick Start options that you can select from to populate pre-configured fields, filters and, visualizations in the chart builder. The Quick Start options will vary depending on the data set you have selected.
Quick Start options for the Opportunities data set
These pre-built templates are a great starting point for building custom charts, as you can add and modify elements to suit your needs. Use the instructions below to further develop a pre-built option or build your own chart from scratch. As you are building, you can bring up the Quick Start options at any time by clicking the lightning icon above the search field at the top of the picker.
Building custom charts
Custom charts consist of a data table visualized using a specific chart type. The chart can also have filters added and applied to refine the data in the table.
Think of the data table (in the 'Data' section) as the foundation of the chart you are building. The data table will populate with data fields selected in the picker. The fields available in the picker will depend on the data set you selected when you first opened the Data Explorer.
Adding fields to the data table
Click a field in the picker to add it to the data table. When you select a field, it will appear as a column header in the 'Data' section of the builder.
Data fields will appear highlighted in the picker when they have been selected for use in the chart.
Data fields will be added in the order that they are selected. Measures (i.e. aggregated fields) will always be aligned to the right side of the table.
||Data points will not appear in the table until you click the Run button at the top of the builder.|
Reordering fields in the data table
To reorder fields in the data table, click and drag the column header in the 'Data' section of the builder. Only data fields of the same type can be reordered (i.e. measures can only be reordered in relation to other measures, dimensions can only be reordered in relation to other dimensions).
Pivoting by fields in the data table
Pivoting can be used to summarize large data sets. Pivoting by a data field will show the distribution of the data in the table by the values in the pivoted field. For example, say you selected the 'Posting name title,' 'Opportunities Count' and 'Stage name' fields from the picker and added them to the data table.
|Posting name title||Stage name||Opportunities Count|
Pivoting by the 'Stage name' data field would show the distribution of opportunities across each stage of the pipeline, grouped by posting title.
|Stage name||Stage 1||Stage 2||Stage ...|
|Posting name title||Opportunities Count||Opportunities Count||Opportunities Count|
To pivot by a data field click the right angle arrows icon next to its name in the picker.
Alternatively, click the gear icon in the column header for that field and select Pivot from the menu that appears.
Remove a pivot by deselecting the right angle arrow icon or by clicking the gear icon and selecting Unpivot.
||Note that data in the table will not be pivoted until you click the Run button at the top of the builder. Also note that pivoting may limit the types of visualizations you can choose from. For refer to this video on guidelines for pivoting to learn more.|
Sorting the results of fields in the data table
Click the arrows in the column headers to sort the results in ascending or descending order.
Removing fields from the data table
To remove a data field from the data table, deselect it from the picker or click the gear icon in the column header and select Remove from the menu that appears. Note, if you have added a data field as a filter, removing it from the data table will not remove it from the 'Filters' section. To clear all fields and filters in the builder, click the gear icon (⚙) in the upper-right corner of the builder and select Clear fields and filters.
Once you have added and organized all required fields in the data table, you will next need to add filters. Most data fields in the picker can be added as filter criteria to a chart. In fact, some of the fields in the pickers can only be used as filters.
To add a data field as a filter, hover over it in the picker and select the filter icon.
If you wish to use a field that you have included in the data table as a filter, click the gear icon on the column header and select Filter.
Once a data field has been added to the 'Filters' section of the builder, you can configure the logic for the filter using the operator menu. Most filters allow you to connect multiple parameters using OR (if the operator is positive - e.g. "is equal to") and AND (if the operator is negative - e.g. "is not equal to") conjunctions, while some filters (e.g. Yes/No filters) work in a binary fashion.
To remove a filter, click the 'X' icon next to the filter in the 'Filters' section or deselect the filter icon next to its name in the picker. To clear all fields and filters in the builder, click the gear icon (⚙) in the upper-right corner of the builder and select Clear fields and filters.
Once you have populated the data table and applied all necessary filters, you ready to choose a how to visualize your data. Start by expanding the 'Visualization' section of the builder and selecting from the chart options in the section header.
||The visualization will not generate until you click the Run button at the top of the builder.|
The most appropriate visualization option will depend on the type of data with which you are working. In general, it is best to use the simplest visualization option possible to convey the insight you are trying to get across in your chart. Below is breakdown of commonly used chart types and the insights they are best-suited to convey. Note that some visualization options may not be available, depending on the contents and organization of your data table.
|Chart type||Best use|
|Column and bar charts||Comparing categories|
|Line charts||Comparing values over time (≤ 5 categories)|
|Area charts||Comparing cumulative values (≤ 5 categories)|
|Tables||Comparing exact values|
|Histograms and scatterplots||Highlighting the spread of values|
|Pie charts and donut multiples||Comparing parts of a whole (≤ 5 categories)|
Once you have selected a visualization type, you can fine tune how it is displayed by clicking the gear icon (⚙) in the section header. In the 'Edit' menu, you can configure aesthetic elements in the selected visualization such as series positioning (e.g. stacked bar), value labels, grid lines, and axis orientation.
||The default Lever color palette is optimized for ADA compliance. If you are making changes to the color palette used in your visualization, we advise checking to ensure that the chart can still be understood by color blind viewers.|
Saving custom charts
Before saving a custom chart, be sure to click the Run button at the top of the builder one last time to refresh your data table and filters. To save a custom chart click the gear icon (⚙) in the upper-right corner of the builder and select Save from the menu that appears. From here you can choose to save the chart as a new dashboard, save it to an existing dashboard, or to save the chart as a Look.
Saving a custom chart to a new dashboard
Input a title for the dashboard and click Save.
To view the chart on the newly created dashboard, click the View dashboard link in the banner that appears at the top of the builder after the modal closes. The chart will have the same name as the dashboard, but you can edit the title of the chart once it is saved to the dashboard.
Saving a custom chart to an existing dashboard
Input a title for the chart, select the dashboard to which you wish to add it, and click the Save to Dashboard button. Note, that you may need to begin typing the name of the dashboard in the search field in order for the dashboard options to become clickable.
To view the newly added chart on the existing dashboard, click the hyperlinked dashboard title in the banner that appears above the builder after the modal closes.
Saving a custom chart as a Look
- What is a Look?
- A Look is a chart that has been saved as its own discrete item separate from a dashboard. If you save a chart as a Look, it will appear as an entry in your 'Looks' folder. From the folder, you can add individual Looks to existing dashboards. Any edits made to the Look will be reflected on all dashboards to which the Look has been added. Looks are useful if you are generating custom charts that you plan to reuse across more than one custom dashboard. As a best practice, we recommend saving all charts as Looks before adding them to dashboards. In the event that a custom dashboard is mistakenly deleted, you can easily rebuild it using your saved Looks.
Input a title for the chart. If you wish to return to the chart builder, click the Save button. If you wish to view the Look in your 'Looks' folder, click the Save & View Look button.
If you chose to return to the chart builder, you can view the newly added Look by clicking the hyperlinked Look title in the banner that appears above the builder.
For more details on how to manage saved charts, including how to edit a chart once it has been saved, refer to our help article on managing custom dashboards and Looks.
||The Data Explorer refreshes intermittently, which may cause you to lose a chart you are working on if you leave the builder inactive for an extended period of time. We recommend saving charts as Looks regularly throughout the chart building process to avoid losing work.|