Below is some commonly asked questions when building your dashboards.
Renaming Titles:
With your designer licence you have the ability to rename titles of data fields being selected from the data model, making it more meaningful for you and your colleagues to interpret the data.
Count vs DUPCount:
Understanding how Analytics interprets a count on records: Using the example below; if you need to report on the overall completions of an Learning Experience (LX).
- Count - This will only count a single record against each user who has completed that LX.
- DUPCount - This will count all records against each user who has completed the LX - so if a user completes the LX twice this will be reflected in the overall count.
The Pivot table below is applying a Count on the Enrolment Completion Date:
Below shows you how to alter the formula should you wish to apply a DUPCOUNT:
Widget filters vs Dashboard filters:
Analytics offers designers the option to apply filters in 2 ways; widget filters and dashboard filters.
Widget filters:
Widget filters are applied during the build or editing of a widget. To understand the different types of widgets you an revisit for more detail here. Note if you wish to edit or reapply a new filter to a widget you must revisit the original location of the widget as a designer to adjust.
Dashboard filters:
A dashboard can have many filters which will allow you to filter data that applies to multiple widgets applied to your dashboard. To find out how to build a dashboard revisit here for more detail.
Useful tip:
It is possible within a widget to disable dashboard filtering. This means that if there are dashboard filters applied then any widgets set to 'disable' will not allow further filtering of data when dashboard filters are applied:
Above is able example of the dashboard filters being enabled within a widget
It is also possible to disable certain dashboard filters within the widget, therefore, again if data is chosen in the disabled dashboard filter the widget that has that filter disabled will not filter.
Above is able example of the dashboard filter (course name) being disabled within a widget
Dependent Filters:
Using the example below, if you have 2 LX's with the same name, analytics will recognise this as 1 LX, combining the data. It may present as the below within the LXP platform, showing as 2 separate LX's with separate aliases and course ID's (when hovered over).
Therefore useful to note that if applying a filter by the LX name it will combine the data on your results, which may include combining completions etc.
To get around this, should you have a need to separate the data it is possible to further filter the data and in this instance filtering the data further using the course alias name. The alias name will be unique to each LX.
Locking Filters:
You may wish to prevent data being changed when promoting a Shared Dashboard. To do this, a designer should go to the template dashboard and apply the settings below.
When republished this will automatically apply to the shared dashboard preventing those viewing the data to to change it.
Changing colours:
When adding widgets such as pie charts, column charts & line charts, note it is possible to change the default colours that are displayed.
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Example of where colours can be changed within a column chart widget |
Example of where colours can be changed within a pie chart widget |
Below shows a pie chart and how you can update the colours.
Conditioning within Analytics:
It is possible to add conditional formatting allowing you to highlight cells or columns in your visualisations based on a specific condition, making it easier to identify trends outliers or important data points. You can apply conditional formatting to tables, pivot tables and even charts.
Below is an example of adding conditioning rules to a count on statement_ID.
The example above is adding a colour to highlight when a user fails an assessment more than 3 times.
Conditioning on data from the Data Model:
It is also possible to add a condition based on the data provided by the Data model, for example, if a Learning Experience (LX) has 7 objects, the condition could be that when all 7 objects are completed the column would turn green. This would give at a glance who has completed the LX vs who has not.
To do this:
A widget or dashboard filters can then be added to show your required data.