If you're used to working in SAP BW,
you're probably familiar with using hierarchy
and hierarchy node variables to explore your data.
So how do you work with these BW elements in SAP Analytics Cloud?
In the fourth video in this series, SAP Analytics Cloud,
Global Product Evangelist Ingo Hilgefort shows you the way.
This time we will take a look how the query which uses a hierarchy
and a hierarchy node variable
is actually going to surface these variables in Analytics Cloud.
And what that actually means for your story in terms of
choosing the hierarchy for a chart and a table.
So as you can see here,
we have the BW query showing up in the modelling tools.
We have a very, very simple query.
We only have the characteristic Country in the rows.
We have a couple of key figures.
And when we go to the filter part,
we can see we have a hierarchy variable for
Country as well as a hierarchy node variable.
So, first we're going to start building the model,
and then we're going to use the model in the story.
So let's start building the model for the query.
So I'm going to say create model,
going to choose a data source.
And in this case it is a live data connection to our BW system.
We're going to start typing the technical name.
Here's our query.
I'm going to click okay, so as we can see,
we have our three key figures and we have our dimension country.
So I will now save the query.
And as a next step,
we're going to start building a story based on the model.
So I'm going to say create a story.
We're going to choose quickly a canvas,
and we're going to start with the table,
and we're going to choose the model that we just saved.
And similar like the other cases, we're being
presented first with the variables,
the one for the hierarchy and the other one for the hierarchy nodes.
So for now as we can see they are actually optional,
so we can leave it empty.
So we will start with
that situation and then we will come back to the variables.
So we click set. We're going to start actually building our table.
So as we can see we have the dimension country
and our measures. We don't need all the measures for now,
so we're just going to filter it down to the net value. Because we didn't
actually choose a hierarchy, we're being shown the flat representation.
So if we now go in and actually bring back the variables,
we can choose a hierarchy first.
So let's choose the hierarchy
number one. We're not choosing any of the nodes yet, we're going to click Set.
So we can see now our table is changing and it's going to leverage the hierarchy.
So here's now the hierarchy,
we can actually open and close the different parts of it.
Now we are going to bring back the variables
again and we're going to choose a node.
So we leave the hierarchy and we're going to open up the members.
So first of all, you can see now we're actually shown
the hierarchical elements because
the variable for the hierarchy already has a value.
So we're going to choose Europe as the part that we want to see in our table.
So we're going to click OK. We set the variables,
and then you can see now that Europe is basically
becoming our top level node for the table.
And here we can see all the different countries.
So now let's do the same thing for the chart.
So we're going to add a chart here.
We're going to add the measure,
we're going to add the dimension.
And because we did already fill the variable values,
our chart shows Europe as the top node because that's what we selected.
And if we wanted to,
we could drill down Country level.
So let's reset that here.
And what if we, for example,
want to use different values for the chart?
So we can do that by actually overriding
the variable values for this particular chart.
So we can open up the variables.
Say we want to set specific values for this chart.
We remove Europe, we remove the first hierarchy,
and we're going to choose the second hierarchy.
Click OK, confirm it.
And now you can see we have different elements here.
So the chart as well as the table, are based on the same BW query,
but they are using different hierarchies as
well as different hierarchy nodes as it filters.
As you can see SAP Analytics Lab,
it's pretty easy to work with hierarchies in your data.
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