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In the previous blog post, we reviewed the option to define intermediate summaries in the waterfall chart. This time we will look at the ability to leverage several measures, use the option to have pre-calculated measures, and use a breakout dimension – all in a single scenario.

Here the data set we are going to use.

You should notice a few items:

  • The data set has several measures – not just one measure – which we would like to leverage as part of the waterfall chart.
  • The data set contains 2 dimensions : Calendar Month and Product.
  • The data set contains already pre-calculated measures, meaning that the measures that are provided are already the delta-values, so the chart doesn’t have to calculate those anymore.

 

After we uploaded the data into a SAP Analytics Cloud model, we are creating a new waterfall chart.

As shown above, you can see that we were able to add all the measures from our dataset into the Waterfall chart.

Below shows the chart builder panel.

With those new options, you can now add more than a single measure to the Waterfall chart configuration and you can also define the order of measures. In our given example we have “In Stock” as first measure and “Salable” as last measure, which means that those two measures will be used as Start and End of our waterfall chart.

In addition, because we have multiple measures as part of the definition, the “Variance” option is being disabled, meaning that the Waterfall chart assumes that the data that is being used already represents the delta values.

Now we are adding the Calendar Month as first dimension to the Waterfall Chart and because we have multiple measures, its important now to understand the drill behavior.

 

Remember we are starting with a Waterfall chart, which shows the measures we added and the Calendar Month is our first dimension.

 

Now we select the “In Stock” item in the chart and we drill down to the next level. Because we selected a specific measure – In Stock in this example – we will see the measure In Stock broken down by quarter.

Here we select measure In Stock and expand to the next level

.. and here the result, showing us measure In Stock broken down into the four quarters.

if we would use the same expand functionality on the total, then we would see the next level with all measures.

 

and now – last but not least – we also added the ability to add a second dimension (which I would call a “break down dimension), which allows you to add a second dimension.

So lets take Q3 in our sample data set, where you can see we sold the most. So we could add now Product as dimension and see which product contributed the most.

 

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