Filtering options in SAP Analytics Cloud Story Design

In this blog we would like to give you a foretaste of what you can expect in one of our new self-paced learning journeys Designing Stories in SAP Analytics Cloud. The SAP Analytics Cloud offers a variety of filtering options to restrict data to a desired context. In the BI environment, it is almost always about receiving decision support in relation to your own data. But not only filtering can contribute to this, also sorting, conditional formatting, or creating your own calculations can contribute and thus represent an alternative to filtering. Just imagine not filtering your views on those records with revenue greater than €1 million, instead sorting your data on revenue in descending order. In this blog, however, I limit myself to filtering approaches. I will start at the top element, Story, and end at the bottom of a single column in a table, or data point in a chart. Filtering in stories can be created at different levels of the story. Thus there are:  

1. Story- Filter
2. Page- Filter
3. Widget-Filter
4. Column- Filter

I will introduce these filter options below. 

Story-Filter  

Story filters restrict all pages of a story to specific values of dimensions. They can only be added to the story in edit mode and is located in the tools section. 

As soon as you have selected the button, a button appears above the page navigation that allows you to store dimensions or key figures for filtering. The result of a story filter is an input control. 

Story filters can be converted into page filters in classic reporting, but this is not yet possible in optimized reporting. In addition to this method, there is also linked analysis, which makes it possible to filter a complete story based on an existing table or chart. In the corresponding dialog window, the highlighted option is selected and the filtering is applied to the entire story. 

Page-Filter 

Page filters are filters applied to all widgets on the given page. They are also only available in the edit mode of a story. And are generated via an icon in the menu bar. 

Page filters always appear in the story below the page navigation but above the page itself. 

Widget-Filter   

Widget filters are filters that apply only to a specific widget. They can be created by right-clicking on a widget or in the designer. In charts, they are sometimes also referred to as chart filters. 

Most filtering consists of restricting a dimension to its characteristics and possibly doing the same with other dimensions. So if more filters are added to a widget again and again, they are all always active, which means there is an AND link logic. Sometimes, however, OR links and nesting may also be required. For example, you want to show sparkling water in the state of Nevada and orange juice in Oregon. 

If only both countries and both products were stored in the filter, you would get a list with four entries. However, to get the above list, you use advanced filtering. This entry (Advanced Filtering …) is selected in the Add Filter area.

Column-Filter 

The term column filter is to be understood more as a conceptual designation to make the filtering options of the SAP Analytics Cloud easy to understand. Within the SAP Analytics Cloud you will not encounter this filter under so, rather it is a functionality that can be found within the SAP Analytics Cloud in the area of calculations, because these are referred to there as restricted key figures. The term restricted key figure is quite appropriate, because filtering and restrictions are often used synonymously. If a key figure is restricted, then one or more dimensions are filtered for specific characteristics of this dimension. In fact, sometimes you have to make a decision between applying a widget filter or working with a restricted metric. Imagine you want to display the sales of Germany and Italy side by side. Then you can also create a real cross table, i.e. the object Country (here Location) is included in the column axis and then filtered for the two countries Germany and Austria. So we are dealing here with a widget filter. 

Almost the same display as before is created if two restricted key figures are generated instead. The creation of a restricted key figure is always started in the Designer at the point where the key figures of the model can also be stored. In this example, the key figure Days Orders to Receive is then restricted once to the value “Germany” and then again to the value “Austria”. 

Compared to widget filters, restricted key figures are more complex to create, but you have more freedom in visualization. You can only store a sorting on a specific column here, as you can see in the following example. Here the table is sorted in such a way that those sales managers whose turnover in Austria is the highest are listed first. The table shown (see illustration) contains an indication of their sorting at the top left. 

Calculations on restricted key figures  

Furthermore, you can calculate with limited key figures and thus, for example, receive the turnover of the entire world without Germany and Austria. In the case of a restricted key figure, the turnover restricted to Germany and Austria is deducted from the “unrestricted” turnover. Restricted key figures are therefore used as formula components in Calculated Measures. 

The possibilities presented here are often supplemented by the possibilities that the data models bring with them. For example, a live model on an SAP BW Query can contain property value variables and thus also filter your entire story or just a specific widget within your story. An SAP Business Objects universe can contain parameters that then behave very similarly to the variables of an SAP BW query. 

If you are interested in learning the key features of SAP Analytics Cloud Story Design like filtering, sorting, and grouping data in tables or charts, check out our new learning journey Designing Stories in SAP Analytics Cloud.  

Fill the gap through upskilling and enjoy SAP’s learning offerings on the SAP Learning site. This article is created and brought to you by SAP Product Learning CoE experts! 

Written by Michael Melters