SAP Lumira – Calculations Best Practices
Version 1.2
April 2015
Andreas Krause, EMEA Center of Excellence for BI
SAP LUMIRA – CALCULATIONS BEST PRACTICES
Contents
Grouping Calculations ................................................................................................................................... 3
Time dependent Calculations ....................................................................................................................... 8
Currency Conversion Calculations .............................................................................................................. 21
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SAP LUMIRA – CALCULATIONS BEST PRACTICES
Grouping Calculations
With SAP Lumira you have the ability to create groupings based on existing attributes. This is very useful
especially when business users want to have another view on the data and want to have the measures
aggregated on data organized in different ways as provided by the source system.
In the example below you have the option to group existing values of a dimension with the grouping
functionality available in with the manipulation tools.
With pushing the “Group by Selection” button an interface opens to group and organize the values on
your requirements
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SAP LUMIRA – CALCULATIONS BEST PRACTICES
As a result the values are grouped and shown in a new dimension as illustrated in the next screen.
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Often there is also the requirement to group values of a dimension based on values of a measure. As
example you want to group the values of the category dimension based on a range of the gross margin
measure. You want to group the categories in a new category where in group A are the categories with
the highest margin above 10 000 €, in group B are the categories within a range between 10000 and
1000 €, in group C are the categories between 1000 and 100€ and finally everything else below 100€ in
group D. The example below now describes how to define the grouping to achieve the required groups of
categories.
To achieve this you need to define a new calculated dimension (in this example called “Margin Groups”)
via the interface for creating a calculation.
Within the editor interface you need to apply formula based on the category dimension:
if {Gross Margin} < 100 then "D" else if {Gross Margin} < 1000 then "C" else if {Gross Margin} <
10000 then "B" else "A"
The formula groups the values based on different ranges e.g. for the group “D” all values below 100, for
group “C” all values between 100-1000, for group “B” all values between 1000-10000 and finally for group
“A” all values above 10000.
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After defining the formula the result should looks like follows:
After you created the calculated attribute you can show the categories belonging to the different A, B, C
and D margin groups as required. In the example a tree-map visualization is used to show the members
of the different groups
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In addition you can use the newly calculated attribute to create a new calculated measure defined as a
“Count” to count all members belonging to the different margin groups.
With the calculated measure you have now in addition the option to count the number of members
belonging to each margin group as shown below in the column chart.
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Time dependent Calculations
Another important area is to be able to create time dependent calculations. A simple example is a
required Year-to-date vs. Previous Year-to-date comparison of a measure. In the following section a
possible formula is explained to create YTD and PYTD calculation.
Again you can use the interface to create a new calculated dimension.
After opening the interface following formula is applied to calculate the Year-to-Date values:
if Year({Date})=Year(CurrentDate()) and {Date} <=(CurrentDate()) then {Gross Margin} else 0
The formula compares the Year value from the date dimension in the dataset with the year value of the
actual date which is available through the CurrentDate() function. In addition all dates which are smaller
or equal to the current date are compared. With this comparison it is ensured that all datasets with a date
older or equal to today are considered for the year-to-date calculation.
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One of the functionalities in SAP Lumira allows you to edit a new created Calculated Dimension. For this
you just need to hit the preference button of the dimension in the dimension and select Edit. This allows
you to edit an existing formula without the need to recreate it again as in older releases.
In the next step the Previous-Year-to-Date values are calculated with following formula:
if Year({Date}) = Year(CurrentDate()) - 1 and DayOfYear({Date}) <= DayOfYear(CurrentDate()) then
{Gross Margin} else 0
The formula compares the Year value from the date dimension in the dataset with the year value of the
actual date -1 year which is available through the CurrentDate()-1 function. In addition the month
numbers which are smaller or equal to the month of the current date are compared. In the last part the
day numbers of the previous year which are smaller or equal to the day numbers of the current year are
compared. With this comparison it is ensured that all datasets with a date older or equal to the same date
last year are considered for the previous year-to-date calculation.
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Column YTD Gross Margin dimension shows only values up to the current date of 2013.
At the same time column PYTD Gross Margin dimension shows only values for 2012 up to the current
date.
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To finally use the calculated values for visualizations you need to create a measures like shown in the
screen below.
Now the YTD and PYTD measures are available and you can use it for comparison in a column chart.
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Beside Year-to-Date and Previous-Year-to-Date calculations it’s also important to get the calculations per
Quarter or per Month. Below you can find the calculation formulas for these periods:
Quarter-to-Date:
if Quarter({Date}) = Quarter(CurrentDate()) and {Date} <= (CurrentDate()) then {Gross Margin} else
0
Previous-Quarter-to-Date:
if Quarter({Date}) = Quarter(CurrentDate())-1 and DayOfYear({Date}) <= DayOfYear(CurrentDate())
then {Gross Margin} else 0
Month-to-Date:
if Month({Date}) = Month(CurrentDate()) and {Date} <= (CurrentDate()) then {Gross Margin} else 0
Previous Month-to-Date:
if Month({Date}) = Month(CurrentDate()) - 1 and DayOfYear({Date}) <= DayOfYear(CurrentDate())
then {Gross Margin} else 0
The process to apply the formulas is the same as described above for the YTD and PYTD calculations.
Another important use case is to compare data from two different time periods for example a Year over
Year or Quarter over Quarter comparison. The goal is to compare the results between the different time
periods.
In the following example it is explained how to calculate a comparison of the Gross Margin between the
different Quarters.
Again you can use the formula editor and create first a Calculated Dimension
For each required Quarter you need to create a separate Calculation to only get the results of the specific
Quarter. The formula to apply in this example looks follows:
if {Year-Quarter} = "2014-Q1" then {Gross Margin} else 0
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As a result the column Gross Margin Q1 2014 only shows the values for Q1 2014.
You can repeat the calculation with the other required Quarters for the comparison.
Gross Margin Q2 2014: if {Year-Quarter} = "2014-Q2" then {Gross Margin} else 0
Gross Margin Q3 2014: if {Year-Quarter} = "2014-Q3" then {Gross Margin} else 0
Gross Margin Q4 2014: if {Year-Quarter} = "2014-Q4" then {Gross Margin} else 0
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As a result you should have now four new Dimensions each with the values for its own Quarter
In the next steps you have to create a Calculated Measure out of each Dimension.
The result should show now four new Measures
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Now you can use the new Calculated Measures to show a comparison of the Gross Margin between the
different time periods. The example above shows a simple bar chart displaying the Gross Margin of the
four Quarters.
Additional it’s interesting to see the delta or variance between the different time periods for a certain
dimension. In the example below you can see the 2014 Quarter over Quarter Gross Margin for the
different Product Lines in a table view.
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The next step is to create a variance between each quarter. In the raw data column view below only the
data for the calculated Quarter is available e.g. in the screenshot it’s only Gross Margin 2014-Q4 having
numbers. All the other calculated quarters are showing 0.00 as value as they only have valid numbers for
their calculated quarter. Lumira doesn’t support cell references or “IN” calculations in the formula
language to transpose the values of each quarter side by side.
To achieve a variance calculation you need to use a different approach. A possible approach is to export
the dataset from the table as a new dataset and map it against the Product Line Dimension in the original
dataset. With the mapping of the dimension “Lines” and applying the filter again to 2014-Q4 it is possible
to calculate the variance between the different quarters. Below you can find the step by step description
how to achieve this.
First step is to export the current table view as a new dataset
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Go back to the Prepare room to merge the exported dataset back to the original dataset.
In the Merge Data Dialog change the Lookup Dataset to the one with the exported dataset from the table
visualization.
Afterwards you have to map the dimensions for Lines as the key columns to merge the exported dataset
back into the original dataset
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Now the Gross Margins of 2014-Q1 – 2014-Q4 are available in the original dataset. As the mapping was
done only on the Line dimension the values are only valid for exactly this dimension. There are no
aggregations of the measures possible to other dimension levels or combination of dimensions. As you
can see below one of the challenges is that all dimensions which enable a more granular level are going
to duplicate the values e.g. for Product Line “Jackets” there are multiple Categories like “Boatwear” or
“Fancy fabric” which are going to create wrong results when aggregating the measures again to the Line
dimension level
To avoid this behavior the measures which are used now for a variance calculations must not be
aggregated. To achieve this, you need to set the aggregation function for the measure to “none” as
shown in the screenshot below.
With this setting the measure is no longer aggregated and when you now use the “Line” dimension the
values of the merged measures are showing exactly the same values as the ones from the exported
table.
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Table with exported measure values:
Table with original measure values:
As now every column of the merged measures has now a value for each cell, you can create a calculated
dimension for the variance.
The formula for calculating the variance (as percentage value) is following:
{Gross Margin 2014-Q4_Sum} / {Gross Margin 2014-Q3_Sum} * 100
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After you created the calculated dimension the dimension has to be turned into a measure
Again, to avoid wrong aggregations and wrong values the aggregation has to be set to “None”
The result is then the variance between the different quarters e.g. here the variance of the Gross Margin
between Q4 and Q3
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Currency Conversion Calculations
A requested scenario is to setup currency conversion from Global currency to local currencies or vice
versa.
An option to include currency conversion in Lumira is to use the logic provided from the semantic layer of
our SAP BusinessObjects BI 4 Suite or to leverage the currency conversion functionality from SAP HANA
while connecting in online mode.
Sometimes the possibility to convert the currency is simply not included in the semantic layer or in SAP
HANA. In case Lumira is connected to local data sources it is not available at all so you need to define a
solution within Lumira.
To be able to provide currency conversion functionality the currency data needs to be available. A good
source for currency codes and conversion rates you can found on http://www.oanda.com/currency/table.
As shown on the screen below on this webpage you can define your base currency and get the actual
conversion rates for selected (or all) currencies in the required format. In the following section the data is
downloaded as a .csv file.
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To be able to use the currency table the base data set needs to have the local currencies included like
shown in the next screen. The example shows the use of Euro as global and Dirham from the United
Arab Emirates.
As first step the base data needs to be merged/joined with the currency table. For this you need to add
the new data set into Lumira.
Then the data source type and file has to be selected.
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A preview of the selected data set is shown in the next screen
After adding the data set into Lumira the base dataset needs to be merged/joined with the currency table.
For this you have to use the merge operation..
In the merge screen select the key columns to enable the join operation. The key columns in the example
are the local currency column within the base dataset and the currency code from the currency table.
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The result of the merge operation you can see in the next screen. The new added columns are
highlighted in red.
The next step is to apply the calculation for the currency conversion. For this you need to create a new
calculated measure.
Column Units/ 1 EUR contains the currency rate factor from Euro to the local currency. The formula looks
like:
{Gross Margin} * {Units/1 EUR}
With this formula the actual Gross Margin available in Euro is multiplied with the currency rate of the local
currencies.
In case the Gross Margin is only available in local currency and it’s required to calculate a common or
company currency it is also possible to do this. As the currency table includes in addition the conversion
rate from the local currencies (column EUR/1 Units) to Euro following formula can be applied:
{Gross Margin} * {EUR/1 Units}
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The screenshot below shows the definition of the conversion from company currency to local currency.
The new created calculated measure called “Gross Margin in local currency” is now available in the
measures panel.
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You can now use the measure to visualize the Gross Margin in local currency of the selected country like
in the column chart below.
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