The document addresses the challenges of non-standard column names in SAP data when exporting reports from different plants. It suggests solutions for standardizing column names to facilitate seamless data switching without query refresh failures. The proposed methods include modifying M code to accommodate variations in column names or renaming headers directly in the query.

1. Power-Ups
Non-standard column
names

2. Overview
For this post our assumptions are:
● You are the “Finance guy/girl that knows data as well”
● You do not have access to a fancy data warehouse
● You are downloading / exporting data out an ERP system
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3. Problem
● Column names can vary between plants or legal entities in
SAP
● For example an accounts payables report for plant 1 and
plant 2 may have the identical number of columns but the
column names may not match
● This can create issues if you are building a BI file that
allows the users to switch between data sources
● Non-standard column names would cause the query
refresh to fail each time you switched data sources
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4. Example
● The data tables below are similar but note the spelling on the
second column…”Amt” and “Amount”.
● I have saved two separate files “Plant1” and “Plant2”. The files
are saved as Unicode text files since this is a likely format out
of SAP.
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5. 5
Load Data /
Parameters
● I have created a path and
parameter to load the data.
● See my prior post on creating
Parameters.
● Note however that the rows
have been promoted as a
header and “Amt” appears in
the second column

6. 6
Switch Data
Sets
● The current selection is Plant1,
the user should now be able to
select Plant2 data…right?
● The query refresh fails!
Because the second column in
Plant2 is named “Amount”.
● The error message below
shows that the query is looking
for an “Amt” column in the
Plant2 data set that it can not
find.

7. 7
Rename Headers
● What if I used the same query but I changed the column name from
“Amt” to “Amount”?
● The query still fails because
in the preceding steps,
before renaming the column,
the query is already looking
for an “Amt” column header.

8. Solution 1
● Get rid of the step where the headers are promoted and then
you can then rename each column to the appropriate name.
● There is only three columns, so renaming is workable but what
if there was 20 or 50 columns? Renaming 50 columns when
there is only a standardization issue with one column is
wasteful
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Rename columns

9. Solution 2
● Keep the promote headers step. This way you don’t need to
rename 49 columns and
● Change the M Code to search for either “Amt” or “Amount” and
when either value is found the column is renamed as “Amount”.
Any missing fields are ignored.
● = Table.RenameColumns(#"Promoted Headers",{{"Amt",
"Amount"},{"Amount","Amount"}}, MissingField.Ignore)
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10. 10
Ta-dah!
● You have identified the non-standard column
● You have efficiently standardized the column names between
the two data sets with some M Code
● The user can now switch between data sets with no issues.

11. Thanks!
I am Johann Krugell
A practical guide to “Power-Up” your analysis
You can find me at @JohannKrugell@linkedin
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12. Credits
Special thanks to all the people who made and
released these awesome resources for free:
● Presentation template by SlidesCarnival
● Photographs by Unsplash
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