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Performing Complex Data Transformations

Below is an example of complex data transformation we have done for one of our customers

Source File


Desired result of transformation


The hurdle with this report is the floating rows. Each material number may or may not have the same number of rows of information. Also, required information is on different lines - for example Min/Max stock level has 2 values on different rows on the input file and we need it to Transpose on output into 2 columns on the same row. Consumption is the same way.

It is rather a complicated example and it gives a very good demonstration of software abilities

  • Data flows from the left to the right
  • Data reader reads the data
  • it ignores number of header columns since we do not need them
  • Data Validator removes empty lines
  • Data Transformer 1 extracts the columns we need
  • Data transformer 2 helps us to calculate values distributed on several rows.
    We use combination of Sequence number +calculation function
    Sequence number is reset back to 1 when product number changes,
    so when sequence number =1 then we have min value when 2 max value etc
  • Next we use data grouper to the get the last line from the group and
  • last data transformer for actual mapping

Data transformation Screenshots

Click on thumbnail to see the screenshot

Transformation Result Transformation Result Transformation Result Transformation Result Transformation Result

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Visual Importer ETL  saved us 25-30 hours per month. Much of that comes from being able to build in error checking into the scripting. I've even been able to script corrections that run on the fly triggered by the error checking on incoming order files.

Gene Kovacs,
Director of Technical Business Operations,

Our customers






Australian Rugby Union
Databases we work with