Global Dashboard Filters

Owned by Philipp Marbach
Last updated: Nov 10, 2022
6 min read

Global Dashboards

Global Dashboards visualise data from multiple data collections in one dashboard. The fact that charts on this dashboard are build form multiple data collections means that filters become a bit more complicated than on a simple data collection dashboard.

For global dashboards a “filter mapping” is required in most cases.

 

  1. To add a filter to a global dashboard, click on the three dots on the upper right corner, select dashboard, click on the three dots again and select “Edit filters”.

2. In the window click on the “+ Add” button to add a filter.

 

3. In the window that pops up you can add a name for the filter. Unlike in the window for the simple data collection dashboard filters, the data collection is not pre-selected because a global dashboard can visualise data from multiple dashboards.

 

4. In this example, we add a filter for a tourism region. The data collection “Antworten” has been selected which contains the column or elements “tourism region” that we want to filter for.

5. For the filter path select the item you want to filter for, in this case the tourism region. Similar to the data collection dashboard filters, select the top item of the specific topic you want to filter for.

Here we only select the tourism region and don’t click further down the selection to the name.

6. Once you selected the item you want to filter for, click apply to view all the filters you have added so far. You have the option to add multiple filters simply by repeating the steps above. Once you have added all the filters you want click on the apply button to add them to your dashboard.

7. If you now click on the filter button on the dashboard, a pop-up opens which will allow you to use the filter.

8. This is where the filter mappings become important. Using the example from above where we selected the item “tourism region” from the “Antworten” data collection, if you use the filter for tourism region now, the filter will work only for those charts whose aggregations are build from the data collection “Antworten” as this is the path that the filter knows how to use. So your dashboard might look like this:

 

The difference between the “No data” and working charts is that for the “1 Stern” chart, the filter has not been mapped.

9. To map filters and make sure to they work across the different data collections on a dashboard, go into the edit dashboard mode by clicking on the three dots on the upper right corner, and selecting

dashboard. The go down to the chart for which you want to do the filter mapping. Click on the three dots and select “filter mapping”.

 

 

10.   In the filter mapping window you can see the data collection from which a filter is mapped and the

aggregation form which the chart you want to map the filter for has been created. In the picture to the right you can see that the data collection and the aggregation for the two first items “Betriebsart” and “Jahr” are both the same: TRMB. This means that no filter mapping is required here as the filter searches within the

same data collection it was created from, so these two items are essentially simple data collection dashboard filters. The third item “tourismusregion” or tourism region has two different codes for data collection and aggregation. This means that the filter path needs to be mapped.

11.   To do this, click on the little wrench on the right sight and you will have the option to select a replacement path for the filter. In the image below, the part in the yellow circle is the set-up of the current filter that you entered when you created the filter. The green box contains the

 

 

This path shows the filter the path to the item you want to filter for. For example in the “Antworten” data collection the tourism region might have been simply a questions in the data collection, in the chart you are currently mapping the tourism region may be in a hierarchy below another geographic features, meaning that the tourism region is part of a state, which in turn is part of the country. What you are doing with the filter mapping is showing the filter where to find the item you are looking for in the data collection from which the aggregation for your chart is built. The green box is the filter mapping you need to do for the current chart that is built from a different data collection, here you need to show the filter where to find the item in the new data collection for which you are mapping. Simply select the item you are filtering for as in the previous cases.

 

 

 

12.   Once you selected the item, click on apply again and do the same for other filters that require mapping. Click on apply again to use the filter mapping for your dashboard.

13.   If you open the filter mapping window again, you should be able to now see the replacement path.

14.   Click apply again, and from now on you can use the filter across the dashboard for all the charts for which the filter has been mapped.

 

15. Ignoring filters

Sometimes you will add a filter for an item that is contained in one data collection but not in others that are used for your dashboard. For example, in the image above the filters “Jahre” and “Tourismusregion” are used in all data collections on the dashboard and can be mapped and used across the charts. The item “Betriebsart” is used in the data collection “LKA” but does not exist in the data collection SD, which has been used to build the chart we are mapping filters for. This means that it is impossible to map the filter as the item does not exist in the SD data collection. In this case there are two options: a) not mapping the filter and “no data” will be displayed in the chart, or b) ignoring the filter and displaying the same data without the “Betriebsart” filter being applied to the chart. To ignore a filter, click on the wrench on the right side, and in the pop-up window at the bottom you can select “Ignore”, toggle the button to active, click apply and the filter will be ignored. Chose whatever makes most sense to your dashboard.