This is part of the SAP Lumira Discovery Series of blogs.
Linked Analysis is one way we can dynamically interact with data across multiple charts. It allows us to create relationships between charts (from the same or different pages) within a story. When we select dimensions on a source chart, it will affect the target charts.
We can link between charts / tables based on same data set or different datasets that contain linked dimensions. Linked Analysis is like Element Linking in BO WEBI, except we cannot apply the links for the whole page which includes the source table / chart.
Pre-requisite for Linked Analysis
There should not be an existing dimension based filter that will be also be used for the linked analysis. The Lumira document should contain more than one visualization. In the below example crosstab (“Revenue”) is the source table and column chart (“No of Issues by City”) is target chart.
Linked Analysis between same dataset
Right click on the source table where we want to create linked analysis.
On the list of option please click option. (Refer the below screenshot)
Select “City” dimension to link the “Revenue” table and “No. of Issues by City” chart.
After selecting the dimension, the visualization whichever can filter data according to the selected dimension will be available for selections, remaining will be greyed out.
Select the target page (if you have multiple pages) and target chart / table to get affected by the selected dimension and click ok.
In the above scenario select Page-01 and check “No of Issues by City” check box.
Successfully, link has been established between “Revenue” table and “No of Issues by City”
- Go to
- Click on “United Kingdom” country from “Revenue” table.
- Data is filtered according to the selected country and “No of Issues by City” chart displays only city of “United Kingdom”.
Note: – If the linked dimension is not present the in the target chart / table, the data will get filtered for that dimension and the result will reflect in the target chart / table.
Table – Click on the table column header to reset the selection
Chart – Apart from data, click anywhere in plot area to return to the starting position
Linked Analysis between different dataset
Follow all the above steps except Step 2. In Step 2, we need to select on the linked dimension from different data source, if we choose other dimensions apart from Linked dimension then the visualizations are greyed out in the options.
For how to combine multiple data sources in Lumira Discovery please refer below blog.
Note: – We cannot perform “Linked Analysis” between different data set if no common dimension is existing between data sets.
Editing Linked Analysis
We can change only the target visualization (table / chart). We cannot change the dimension while editing the linked analysis, therefore it remains disabled.
Follow the below steps to edit the existing Link on “Revenue” table.
- Right-click on the “Revenue” table (Source Visualization).
- Select Linked Analysis -> Edit Link (Refer below screenshot)
Select “Quantity sold by Manager” from Page 02 and unselect “No of Issues by City” from Page 01
To change the dimension in “Linked Analysis” we need to delete the existing link and create a new link on new dimension. At present we do not have a direct option to change the linked dimension for linked analysis.
Deleting Linked Analysis
Select Linked Analysis -> Delete Link option to delete the existing links.
The Linked Analysis feature is very useful in Lumira Discovery. With linked analysis, it is easy to select dimensions (that may include hierarchical data) on a source chart and its related actions occur in the target charts that we want to include in the analysis.
Note: We cannot perform linked analysis across stories. Linked analysis is available only within same story.
More details on the individual features can be found by clicking on the hyperlinks/title.
This information is based on the current product and roadmap and is bound to change.
Get your business users trained on more best practices of SAP Lumira Discovery and Designer.
Want to know more? Click here to get in touch.